# The plan, and how the interface sits on Paperclip Written 2026-11-10, after a wrong turn: I split every workspace into three panes without being asked, and it broke the working layout. It has been reverted. This document says what exists, what is proposed, and which Paperclip endpoint each thing reads or writes. Nothing here is invented: every endpoint below was called on this machine and answered. ## What is on screen today Seven workspaces, one pane each: `Shell>shell`, `Board>board`, `Work>work`, `Reply>reply`, `New task>new`, `Project>project`, `Repair>repair`. Inside a pane the program draws several panels (Board draws three), and you switch focus with Tab. That is the state that works. ## Paperclip's objects, and where each one is seen | Paperclip object | Endpoint, measured | Where it appears now | |---|---|---| | company | `GET /api/companies/{id}` | not shown; the id is in the project file | | project | `GET /api/companies/{id}/projects` | `Project>project` | | task | `GET /api/companies/{id}/issues`, `GET /api/issues/{id}` | `Board>board`, `Reply>reply` task panel | | blockers of a task | `GET /api/issues/{id}/diagnostics/blockers` | `Board>board`, per row | | comment thread | `GET /api/issues/{id}/comments` | `Reply>reply` | | runs of a task | `GET /api/issues/{id}/runs` | `Work>work` | | activity | `GET /api/issues/{id}/activity` | `Board>board` needs-you tab, `Work>work` | | cost per task | `GET /api/issues/{id}/cost-summary` | `Board>board` detail, `Work>work` facts, `Project>project` costs | | worktree and branch | the task's `currentExecutionWorkspace` | `Work>work` change and facts | | agents | `GET /api/companies/{id}/agents` | `Project>project` facts and limits, by name and budget | | **an agent's runs, company-wide** | `GET /api/companies/{id}/heartbeat-runs` | **nowhere yet** | | **a run's log** | `GET /api/heartbeat-runs/{runId}/log` — 300 KB of JSON lines for one finished run | **nowhere yet** | | **a run's events** | `GET /api/heartbeat-runs/{runId}/events` | **nowhere yet** | | agent pause, resume, wake | `POST /api/agents/{id}/pause`, `/resume`, `/wakeup` | **nowhere yet** | | agent settings | `PATCH /api/agents/{id}` — accepts `role`, `adapterConfig` (the model), `runtimeConfig` (heartbeat), `budgetMonthlyCents`, `status` | **nowhere yet** | So the honest answer to "where do I see the Pi agents working": **you cannot, yet.** The data is all there and the runs are already recorded — 281 of them on this instance — but no screen shows them. That is the largest missing piece, and it is the next workspace. ## Missing: the Agents workspace This is the one the person keeps asking for and it does not exist. Proposed as one pane, the same shape as the others, drawing three panels with tabs: ``` Agents>agents ╭─ agents roster runs ╮ │ Campfire idle │ ● Builder running AUD-163 started 14:12 1m 20s 1 cent │ ● Hub idle last run 13:58 │ ● Documenter idle ╰───────────────────────────╯ ``` - **roster** — every agent: name, state (`idle`, `running`, `needs input`, and Paperclip's own status), current task if any, spend this month, budget. From `GET /api/companies/{id}/agents`. - **runs** — the company's run list, newest first: agent, task, state, what woke it, start, duration, cost. From `GET /api/companies/{id}/heartbeat-runs` (281 today). - **log** — the tail of the chosen run, from `GET /api/heartbeat-runs/{runId}/log`. This is the closest thing to "watching Pi work": the log grows while the run is live, and `lastOutputAt`/`lastOutputBytes` on the run say how fresh it is. Actions, all with the user key, all reversible: - `enter` on a run → its log in the log tab. - `p` pause, `P` resume an agent (`POST /api/agents/{id}/pause|resume`). - `w` wake an agent (`POST /api/agents/{id}/wakeup`). - `e` open its settings (see below). ## Missing: working on an agent — role, model, cost Paperclip owns these, so the interface edits Paperclip, never a local file. One more panel, `Agents>settings`, or a tab inside `Agents>agents`: | Field | Paperclip field | Endpoint | |---|---|---| | name and job title | `name`, `title` | `PATCH /api/agents/{id}` | | role | `role` | same | | who it reports to | `reportsTo` | same | | model (the LLM) | `adapterConfig.model` | same, with `replaceAdapterConfig` care | | heartbeat on/off, concurrency | `runtimeConfig.heartbeat` | same | | monthly budget | `budgetMonthlyCents` | same | | pause / resume | `POST /api/agents/{id}/pause`, `/resume` | separate calls | Two rules that fall out of this and are not negotiable: a change to a model applies to that agent's **next** run, never to one in flight; and a budget change is recorded with who changed it, because Paperclip's audit trail is the only record we have. ## Tool panels: Lazygit, Hunk, a shell, the review Both are installed on this machine and I verified the paths: `/run/current-system/sw/bin/lazygit` and `/etc/profiles/per-user/sam/bin/hunk`. They are **not** to be reimplemented. The proposal is one key in `Work>work`: - `t` opens a chooser: `shell · lazygit · hunk · git log · ocr`. - The chosen tool opens as a pane **in the current workspace**, beside the panel you were reading, and takes focus. - `q` or `esc` closes it and focus returns exactly where it was. - Nothing is created until you ask, so the layout stays as it is today. This is the answer to "I thought we had Lazygit and Hunk": they are installed, they are not wired in, and wiring them in is one pane-opener plus a key. ## The review: ocr is installed and has already run `ocr` is at `/home/sam/.local/bin/ocr`, version `open-code-review v1.13.6`. It is in the project's `bin/merge` and `bin/review`, and it has blocked a real merge: on `AUD-165` it reported a critical finding (`rm -rf "$HOME/tmp"` deleting `/tmp` when `HOME` is empty) and the merge was refused. The Repair screen once said "not on the path" because a pane started by TUIOS gets a smaller PATH than a shell; that was fixed by looking in the usual places. Where it belongs in the interface: a **review panel inside `Work>work`**, showing the last verdict for the chosen task, its findings, and the blocking ones in red. The merge stays a command (`bin/merge`), because a merge is a decision with a lock, not a keystroke. ## Mouse-1 and Switch Measured just now: **not installed** — no `mouse`, `mouse1` or `switch` binary on this machine, and nothing obviously serving them locally. So nothing can be built on them yet without adding software first. Where they would fit if added: Mouse-1 is a small probability model that answers typed questions; Switch turns a state into those questions. The honest use in this factory is **routing and judgement that must be cheap and repeatable** — "is this task ready", "does this comment answer the question", "which agent should take this" — rather than prose generation. That is a later milestone, after agents and the review panel, and it needs a decision about installing both, plus a measurement of whether they are better than the existing cheap model already configured for agents (`omni/deepseek/deepseek-v4-flash`). ## The order I propose 1. **Agents workspace** — roster, runs, log. This is the missing view of Pi working, and it is read-only, so it cannot break anything. 2. **Agent settings** — role, model, budget, pause/resume. First write surface aimed at agents rather than tasks. 3. **Tool panels** — `t` opens Lazygit, Hunk, a shell, `ocr` in the current workspace. 4. **Review panel** in `Work>work` — the last verdict and its findings, beside the diff. 5. **Mouse-1 / Switch** — only after the above, and only after they are installed and measured. Each of the first four is one pane, one program, no change to the working layout. Nothing in this list requires splitting workspaces again. --- # Answers to the open questions, 2026-11-10 **Where settings are set.** `Agents>agents` has a fourth tab, **settings**, which edits the chosen agent: role, job title, model, monthly budget, heartbeat. `enter` edits the field in place, `esc` cancels, and `p` / `P` / `w` pause, resume and wake. Each save is one `PATCH /api/agents/{id}` merged into that agent's existing configuration, so a model change never wipes its folder or instructions. `Project>project` shows spend and limits read-only, because Paperclip owns them and a second editable copy is how two screens start disagreeing. **Spend.** Read from `cost-summary` per task (`Project>costs`, `Board>board`, `Work>work`). The monthly budget is per agent, set in `Agents>agents` settings. There is no company-level control on any screen yet. **Skills for sub-agents.** Not in the interface. Paperclip has the endpoints — `GET /api/agents/{id}/skills`, `POST /api/agents/{id}/skills/sync` with `add`, `remove` or `replace` — so a read-only skills row is cheap and a full editor is a later step. The rule worth keeping: an agent gets the skills its job needs and no more, which the `add`/`replace` model already expresses. **Where work is added.** `New task>new`, which writes a Paperclip task. A second place to write tasks (Tuxedo, a notes file, a card board) would be a second owner for the same fact and is exactly the failure the old project had. Personal notes are different from tasks: if they are wanted, they belong in the project's own `.harness/NOTES.md`, and Tuxedo can read it per project without pretending to be a task board. **`office --host` from another machine.** Not implemented, and the runbook says why: session creation needs a real terminal, so a person creates the session (`tuios new --host nixos-desktop "new test project"`) and then runs `bin/office ` inside it, on the machine that owns the folder. `--host` today only records the host in the project file. Driving `bin/office` on `.27` from `.13` would need ssh plus a remote `bin/board`, which is a deliberate later step, not an accident. **Seeing and switching projects.** Not built. Paperclip has the list (`GET /api/companies/{id}/projects`); what it cannot know is which folder on which machine each one lives in. The proposal: a small local registry of adopted projects (`~/.config/paperclip-harness/projects.toml`: project id, folder, host, session), filled by `bin/office`, and a `Project>projects` tab that lists them and switches by writing the project into the current folder's `.harness/harness.toml`. A project on another machine can only be switched to if the pane can reach it, so it would be shown as `on .27`, not offered. **Artifacts.** Paperclip work products: an uploaded file, a pull request, a preview URL, a commit or a branch, attached to a task by an agent. They are inspectable records of what a task produced. Nothing shows them yet; the natural home is a `Work>artifacts` tab listing them with their links, read from the task's work products. **"Workspaces" in Paperclip.** Paperclip has no workspaces. It has companies, projects, issues (tasks), agents and runs. A *workspace* is TUIOS's word for a page; a *pane* is a terminal inside it. When Paperclip says workspace it means a project's code folder (`currentExecutionWorkspace`), which is the git worktree a task runs in. **Charts.** TUIOS ships `plot` (Go), `loom` and TML. Go is the better fit here because the panels are already Go and the data is already in memory: a spend-by-day chart in `Project>costs` is a few dozen lines against `tuios.dev/plot`, where a TML surface would be a second language and a second round trip. Worth doing once the functional tests pass. **Mouse-1 and Switch.** Still not installed on this machine. Unchanged from the earlier note: they would serve cheap repeatable judgement, later, after they are installed and measured. --- # Findings for the next round of decisions, 2026-11-10 Everything below was measured on this machine. Nothing here is proposed without saying so. ## Skills per agent — the API already models it `GET /api/agents/{id}/skills` returns, for each agent: ``` mode: "persistent" desiredSkills: ["paperclipai/paperclip/paperclip"] entries: [ { key: "company//obsidian-cli", runtimeName: "obsidian-cli--b74ae42966", desired: false, managed: true, state: "stale", sourcePath: "…/instances/default/skills//obsidian-cli", targetPath: "/home/sam/.pi/agent/skills/obsidian-cli--b74ae42966" } ] ``` So Paperclip already models exactly what is wanted: a desired set per agent, a managed set actually installed, and a state (`stale` today for `obsidian-cli` on `Builder`, which is worth fixing on its own). `POST /api/agents/{id}/skills/sync` with `add`, `remove` or `replace` sets the desired set; `replace` is the operation that means "this agent gets these and nothing else", which is how a sub-agent's context is kept small. Company level, there is more: `GET/POST /api/companies/{id}/skills` (the catalog), `/skills/{id}/versions`, `/skills/{id}/audit`, and `GET/PUT /api/companies/{id}/skill-policy` with `/skill-policy/evaluate`, which is a company-wide rule about which skills may be used. Proposed in the interface: `Agents>agents` settings tab gains two rows — **skills** (the desired set, read-only at first, with `add`/`remove` later) and **skill source** (company catalog or the agent's own). A full skill browser is a later screen, not a panel. ## Memory — three different things wearing one word | What | State here | What it does | |---|---|---| | **engram** | installed, `engram v1.16.1`, MCP server mode, no pi MCP entry yet | persistent memory for agents, over HTTP or MCP | | **headroom** | running, `headroom-proxy v0.24.0`, healthy at `192.168.20.13:8787`, memory backend **disabled**, compression enabled | compresses prompts on the way out; it is a proxy, not a store | | **pi memctx** | in use in this session | the memory gateway that injects notes into a prompt | They are not alternatives: engram stores, headroom compresses, memctx injects. For agents, the only lever Paperclip gives us is per-agent configuration — `adapterConfig` (the folder, the model, the instructions bundle) and `runtimeConfig` — so memory is set per agent by pointing that agent at the proxy or the storage it should use, not by a global switch. Proposed: a **memory** row in `Agents>agents` settings showing which of the three that agent uses, read from its adapter configuration; and nothing more until one agent has been run both ways and the difference measured. ## MOUSE-1 - `MOUSE_API_KEY` **is** set in `~/.config/environment.d/10-secrets.conf` (name checked, value never printed). `JEV_API_KEY` is set as well. - No `mouse`, `mouse1`, `jev` or `switch` binary is installed. - The previous project already wrote the policy, in `~/paseo/projects/tuios_coding_harness/plan/*`: MOUSE-1 is **"triage only: label, score, route, escalate. Never a gate, never a permit"**, and explicitly ruled out for deciding a merge or allowing a tool call, because a cheap classifier that fails open on a network error turns a green run into a lie. That policy is right and should be adopted unchanged. Its place in this interface, if it is added: `Board>board` needs-you could be ordered by a MOUSE-1 score, and `Work>review` could use it to pre-sort findings. Never the merge, never an approval. ## Lazygit Already wired: `t` in `Board>board` or `Work>work`, then choose Lazygit. It opens beside the pane, in the same workspace, and `q` closes it. Hunk, Yazi, Neovim, fzf, a shell and ocr are in the same chooser. ## The old `office` command, and what ours is missing The previous project's `office` does four things, in order: 1. makes the folder and remembers the host in `/.harness/host`; 2. runs `new-project` to write the project scaffold — `settings.toml`, one file per role, `verify.sh`, the per-screen notes — **writing only what is missing, never overwriting**; 3. refuses to continue if the TUIOS session does not exist, and prints the exact `tuios new ` line to run; 4. runs its `board` to build or repair the pages, then prints how to attach. Ours does 1, 3 and 4 (with a different file: `.harness/harness.toml`). It does **not** do 2: there is no scaffold, no per-role file, no `verify.sh`, no page notes. That is a real gap and the cheapest useful one to close. ## Dashboard — the API already answers it `GET /api/companies/{id}/dashboard` returns 1.8 KB: ``` agents: {active: 6, running: 0, paused: 0, error: 0} tasks: {open: 8, inProgress: 0, blocked: 4, done: 147} costs: {monthSpendCents: 11, monthBudgetCents: 0, monthUtilizationPercent: 0} pendingApprovals: 0 budgets: {activeIncidents: 0, pendingApprovals: 0, pausedAgents: 0, pausedProjects: 0} runActivity: [14 entries] ``` That is a whole dashboard in one call, and it is cheap enough to poll. Proposal: a `Project>overview` panel showing those four blocks and a sparkline of `runActivity`, drawn in Go with `tuios.dev/plot` rather than embedding Paperclip's web dashboard. ## Not doing Artifacts, as instructed. Nothing about them will be added. --- # Pi agents: how their configuration actually resolves Advice only — nothing here was built. Every fact below was read from the installed code, the config files, or the API on this machine. ## Your picker, and what it really writes `pi-config` is an extension with five commands: `/config-add`, `/config-remove`, `/config-list`, `/config-show`, `/config-setup`. `picker.ts` is the overlay — a filtered list of `~/.agents/skills` and `~/.agents/extensions` showing which are active in the project and which are active globally. The commands write **JSON**, at: ``` /.pi/settings.json ← project settings (the picker's "-l" mode) ~/.pi/agent/settings.json ← global settings ``` and the shape they manipulate is a `packages` array of sources and filters: ```json {"packages": [ "npm:pi-memctx", {"source": "git:https://gitea.lab.audasmedia.com.au/sam/pi-config", "extensions": ["extensions/pi-config/index.ts", "extensions/tavily-search/index.ts"]}, {"source": "/home/sam/.agents", "skills": ["nixos-workflow"], "extensions": []} ]} ``` So yes: this is a stable JSON contract, and anything that can write a file can formulate an agent's context the way the picker does. The question is not *whether* it can be written, but *which one Pi actually reads on a Paperclip run*. ## What Pi reads, in order From Pi's own documentation: - global: `~/.pi/agent/skills/`, `~/.agents/skills/` - **project, only after the project is trusted**: `.pi/skills/`, `.agents/skills/` in the working directory and its ancestors up to the git root - packages and the settings `skills` array - command line: `--skill `, additive even with `--no-skills` Settings merge the same way: user settings, then `/.pi/settings.json`. ## What Paperclip actually runs From `@paperclipai/adapter-pi-local`, a run is: ``` pi --mode json --append-system-prompt --provider

--model --thinking --tools read,bash,edit,write,grep,find,ls --session /home/sam/.pi/paperclips/-.jsonl --skill ``` and before the run it symlinks the agent's desired skills into `~/.pi/agent/skills/`. Four consequences, and they matter: 1. **Skills are already per agent** — `desiredSkills` plus `POST /api/agents/{id}/skills/sync`. That is the supported lever, and it is what the `--skill` directory is built from. 2. **The isolation is not complete.** Injected skills are symlinked into the *shared* global directory and are not removed when another agent runs, and Paperclip does not pass `--no-skills`. So a skill an agent once had can remain visible to another agent. 3. **The tool list is fixed** at `read,bash,edit,write,grep,find,ls`. An agent cannot gain a tool by being given an extension unless the adapter is changed. 4. **Project-local `.pi/settings.json` is unlikely to be honoured for Paperclip runs.** Pi only loads project settings from a trusted path. `~/.pi/agent/trust.json` holds 14 entries and none of them is a Paperclip worktree or `~/paperclip-agents`. Worse, a worktree path changes with every task (`…/worktrees/AUD-165-…`), so there is nothing stable to trust. ## So what is the honest advice - **Agent identity, instructions, model, budget, and skills: Paperclip.** Those are per-agent already and they are what a run uses. The instructions bundle at `~/.paperclip/instances/default/companies//agents//instructions/AGENTS.md` is the real per-agent context control, and it is editable through the API. - **Extensions: one global set, not per agent.** There is no per-agent extension mechanism in this adapter. Pretending otherwise would produce agents whose behaviour depends on which one ran last. - **Folder-level cleverness: keep out of the critical path.** Writing `.pi/settings.json` into a project is useful for *you* when you open Pi in that folder by hand; it is not reliable inside a Paperclip run, because of trust and because worktrees are new paths each time. - **If per-agent extensions are genuinely wanted**, the change is in the adapter: pass a per-agent config directory or `--no-skills` plus an explicit set, and remove stale links. That is a Paperclip feature, not something our terminal can arrange from outside. ## History: yes, and it is richer than the run log - `~/.pi/paperclips/*.jsonl` — **178 files** on this machine, one per run, named `-.jsonl`, and each is the full conversation (session start, model changes, messages). - `GET /api/agents/{id}/task-sessions` — maps a task to its session file and working directory. - `GET /api/heartbeat-runs/{runId}/log` — the run log already shown in `Agents>agents`. - `GET /api/agents/{id}/runtime-state` — the agent's current runtime state. A history panel is therefore feasible without new plumbing: list an agent's sessions from `task-sessions`, open one, and render the JSONL transcript. That is the natural next panel after the functional tests, and it is read-only. --- # Correction: per-agent skills are the design, not an accident The section above gives the wrong impression. Here is the accurate version. ## Each agent has its own skill set, and that is stored in Paperclip `GET /api/agents/{id}/skills` returns, per agent, `desiredSkills` and the entries actually managed for it. `Builder` had its own list; `Documenter` has another. Setting it is one call: ``` POST /api/agents/{id}/skills/sync { "mode": "replace" | "add" | "remove", "desiredSkills": ["company//nixos-workflow", "paperclipai/paperclip/paperclip"] } ``` `replace` means "this agent gets exactly these". At run time the adapter builds a directory from **that agent's** desired set and passes it as `--skill`, and symlinks those skills into `~/.pi/agent/skills/` so the run can find them. So: different agents, different skills, no problem — this is already the supported path and it needs no picker. The caveat I over-stated is narrow: the symlinks stay in the shared global directory after a run, and Paperclip does not pass `--no-skills`, so a skill an agent used once can remain discoverable by another agent afterwards. That is a leak to know about (and a good argument for `replace` plus a periodic clean), not "one set for everybody". Where skills come from: `GET /api/skills/available`, the company list at `GET /api/companies/{id}/skills`, and the catalog at `GET /api/skills/catalog`. A skill there can be assigned to any agent with the call above. ## Extensions per agent: yes, through the command The adapter's configuration document says the agent's command defaults to `pi` and can be set per agent: ``` adapterConfig.command defaults to "pi" adapterConfig.env KEY=VALUE pairs ``` So an agent can be given its own wrapper: ``` ~/paperclip-agents/builder/pi-wrapper.sh: #!/bin/sh exec pi --extension npm:pi-memctx --extension git:https://gitea…/pi-config/extensions/tavily-search/index.ts "$@" ``` and `PATCH /api/agents/{id}` with `{"adapterConfig": {…, "command": "…/pi-wrapper.sh"}}`. The adapter appends its own arguments (`--mode json`, `--session`, `--skill`, `--tools`, `--model`) to whatever the command is, so the wrapper is additive and cannot break the run. `env` is the same lever for environment variables. That is how per-agent extensions become real today: one wrapper per agent role (`builder`, `documenter`, `reviewer`), each listing the extensions that role may use. It also gives a place to set `--no-skills` if strict isolation is wanted, and a place to keep the tool list deliberately small. ## History: three options, in order of fidelity 1. **Open the real Pi session in a pane.** Paperclip writes every run to `~/.pi/paperclips/-.jsonl` and starts Pi with `--session `. A pane running `pi --session ` gives the actual conversation, with Pi's own interface, and can be continued. Highest fidelity, zero new code — a tool-pane entry that takes a file path. Two writers on one session file is the risk, so this is for sessions that are finished, or for a deliberate hand-over. 2. **A read-only transcript panel.** Parse the JSONL and draw the messages in `Agents>agents` as a fourth tab. Integrated, safe, no second process; less faithful than the real thing. 3. **`pi --resume`** in a tool pane, and pick the session from Pi's own list. Simplest of all, but it makes you find the session by eye. `GET /api/agents/{id}/task-sessions` maps task → session file and working directory, so option 1 and 2 both have a reliable index and neither needs guessing. --- # Confirmed: what the picker emulation needs, and what it can actually do Researched by doing it, on this machine, with the board key. Everything below returned 200 or 201 unless it says otherwise. ## The gap, measured | Set | Where | Count | |---|---|---| | what the pi-config picker lists | `~/.agents/skills` | **21** (archify, caveman, nixos-workflow, tuios, …) | | what Paperclip can assign | `GET /api/companies/{id}/skills` | **9** (agentmail, obsidian-cli, paperclip, project-docs, system-architect, …) | So eleven skills a person can see in the picker cannot be given to a Paperclip agent today, because Paperclip has never heard of them. That is the whole problem, and it is smaller than it looked. ## What works, in order 1. **Copy the skill into the company's managed directory.** A local import is refused from anywhere else — `POST …/skills/import` with a path under `~/.agents` returned **403 `skill_workspace_boundary_denied`**, "Import from a configured Paperclip workspace or the company managed-skill directory". Copying to `~/.paperclip/instances/default/skills//` and importing that path returned **201**: ``` {"key": "local/9a9eba3826/nixos-workflow", "slug": "nixos-workflow", …} ``` 2. **Assign it to one agent, and only that agent**: ``` POST /api/agents/{agentId}/skills/sync {"mode": "add", "desiredSkills": ["local/9a9eba3826/nixos-workflow"]} → 200 ``` Verified on `Documenter`: its list went from three skills to four and back to three after a `remove`. Different agents, different lists — as expected. 3. **Extensions have no Paperclip equivalent.** `~/.agents/extensions` holds them; Paperclip's skill model does not. The per-agent lever is `adapterConfig.command`, which defaults to `pi` and is appended to by the adapter. A wrapper per agent that passes `--extension …` and then `exec pi "$@"` is the equivalent of `pi-config` for a Paperclip run. ## So the emulation is this, and nothing more A picker that does what `pi-config`'s does, for Paperclip agents: - **reads** `~/.agents/skills` and `~/.agents/extensions` (the same source the picker uses), the company skill list, and the chosen agent's `desiredSkills`; - **marks** each entry: available but not in Paperclip · in Paperclip · on this agent; - **on choosing** an unavailable skill: copy it into the managed directory, import it, then `skills/sync` it onto that agent; - **on removing**: `skills/sync` with `remove`; - **for an extension**: add it to that agent's wrapper file and point `adapterConfig.command` at the wrapper. That is a small command or one panel, not a new subsystem, and every step above is already verified. ## A change made while checking this `nixos-workflow` was copied into the company's managed directory and imported, so it is now in Paperclip's list and can be assigned to any agent. It is assigned to nobody. Nothing else was changed; `Documenter`'s skills were put back exactly as they were. ## Pi history — the cheap answer is probably enough The instinct is right. Every run is already a file: ``` ~/.pi/paperclips/-.jsonl 178 of them here ``` `GET /api/agents/{id}/task-sessions` maps a task to its session file and folder. So the cheapest useful thing is a tool-pane entry that opens `~/.pi/paperclips` in Yazi, or a pane running `pi --resume` that lists sessions and opens one with Pi's own interface. Both are minutes of work and neither invents anything. A transcript tab inside `Agents>agents` is the integration option: read the JSONL, draw the messages, no second process. Worth doing only if the file browser feels like a detour after a week of use. Recommendation: do the cheap one now, decide later. ## The project's check: `.harness/check.sh` This is a script in the project folder that exits 0 when the project still passes its own tests. It answers "did this change break the project", not "is this task finished". **What decides a task is finished**, in order of authority: 1. the agent, by setting the task's status — this is Paperclip's own model and nothing in our software can overrule it; 2. a reviewer, if a review stage is configured on the task (Paperclip's execution policy); 3. `ocr`, at merge time, which can refuse the change. The project's check is a **regression check** at the same point as a CI pipeline: `bin/merge` runs it in the task's worktree before merging, and again on the base branch after merging, and rolls the merge back if it fails. It never decides that a task is finished. Why keep it at all: an agent says it is done, a review says the diff looks right, and neither proves the build still works. One command does. If a project has no check, `bin/merge` says so and the review decides alone — that is the current state of this sandbox. Naming: `check.sh` is the current name. `.harness/verify.sh` was the earlier project's name and is still honoured if present, so an adopted folder keeps working. `bin/office` writes `check.sh` with a comment explaining what to replace. ## Headroom, concretely Headroom is a proxy that accepts the same HTTP API as the model router and shortens long prompts before forwarding. Measured here: ``` GET http://192.168.20.13:8787/v1/models → 200, 486 models (auto/best-coding, deepseek/…) GET http://192.168.20.13:8787/health → 200, healthy, compression on, memory off upstream (config `openai_api_url`) → http://192.168.20.13:20129/v1 ``` The agents' provider `omni` already points at `http://192.168.20.13:20129/v1`, which is the same upstream headroom forwards to. So headroom can sit in front of it. **How to use it for one agent.** Two steps, and only the second is per agent: 1. Add a provider to `~/.pi/agent/settings.json` (global, once): ```json "headroom": { "baseUrl": "http://192.168.20.13:8787/v1", "apiKey": "", "api": "openai-completions" } ``` 2. Set that agent's model in `Agents>settings` to `headroom/auto/best-coding` (or any model id from the list above). Paperclip stores the model per agent, so exactly one agent changes. **Would it work.** The endpoint answers the OpenAI-style API that Pi's `openai-completions` provider speaks, and lists the models Pi would ask for, so the pieces line up. It is still a hypothesis until one run is made through it: the unknowns are whether the proxy passes Pi's tool-calling requests unchanged, and what compression does to a prompt with large tool results. The measurement is one run: compare cost, duration and result quality for the same task with and without the provider. **Per project is not possible.** The provider is chosen by the agent's model, and agents belong to the company, not to a project. The finest granularity is one agent, which is what the `Agents>settings` model field already gives. ### Measured: what actually fails, and why The earlier claim that "headroom needs an Anthropic key" was wrong. Here is what the tests show. Headroom runs as a container from `ghcr.io/chopratejas/headroom:latest` with `--port 8787 --no-telemetry`, and it is built on **LiteLLM**. Its `/v1/models` lists the same 486 models as the router, and `/v1/compress` works. What fails is a completion through it: ``` router POST /v1/chat/completions deepseek/deepseek-v4-flash → 200, SSE stream, "ok" in 1.1 s headroom POST /v1/chat/completions deepseek/deepseek-v4-flash → 502 {"code":"proxy_error"} ``` `docker logs headroom` shows LiteLLM repeating *"Provider List: https://docs.litellm.ai/docs/providers"* — LiteLLM does not recognise our router's model ids (`deepseek/deepseek-v4-flash`, `auto/best-fast`), so it never makes the call. The same body sent to the router directly succeeds, so the key, the model and the request shape are all fine. **So headroom is not blocked by Anthropic, and not by a key.** It is blocked by LiteLLM not knowing the router's models. To use it as a provider, headroom's own model list has to define them, for example `openai/deepseek-v4-flash` with `api_base: http://192.168.20.13:20129/v1` and our key — a change to headroom's configuration inside that container, not to our software. ### The path that does work: headroom as a tool The `headroom-bridge` extension in `~/.agents/extensions` does something different from a provider: it gives a Pi agent two tools, `compress_for_agent` and `check_headroom`. The first calls headroom's compression endpoint; the second reports whether the service is up. That is the integration that fits: headroom shortens text an agent is about to pass on, rather than standing between the agent and its model. Measured directly, without the extension: ``` POST http://192.168.20.13:8787/v1/compress {"model": …, "messages":[…]} → 200 {tokens_before: 4009, tokens_after: 4009, tokens_saved: 0, compression_ratio: 1.0, transforms_applied: ["router:protected:user_message"]} ``` So the endpoint works and reports its effect honestly; a single long user message is protected from compression, which is why it saved nothing in that test. To give one agent the tool: 1. `~/.agents/extensions/headroom-bridge` needs the `headroom-ai` npm package resolvable by Pi; it is **not** installed in `~/.pi/agent/npm`, so the extension will fail to import until it is. 2. Give the extension to one agent with the extensions picker in `Agents>agents` — `space` writes a wrapper and points that agent's command at it. 3. Then that agent, and no other, has the compression tool. That is the honest position: compression is available as a tool, blocked on one npm package, and it is per agent because the wrapper is per agent. ## Mouse-1, measured The person supplied `docs/MOUSE-1-NOTES.md`, written from measurements on 2026-11-08/09. The facts that shape the design: - `POST https://api.mouse.dev/v1/decisions`, `Authorization: Bearer $MOUSE_API_KEY`, body `{model, state, questions:{id:{type:"choice", instructions, criteria}}}`; the answer returns `choice`, `confidence`, `probabilities`. - **Cold start is minutes.** The first call after idle returned `503 engine_timeout` after 30 s; the retry returned 200 in 13 s; warm calls were 1044 ms then ~489 ms. - The same state and options gave the same choice at ~0.98 confidence. It behaves as a classifier, not a writer. - Proven useful: **failure routing** (redo / stronger model / environment / person), unblock triage, intake clarity, task sizing. Measured in the old project as `bin/route-failure`. - Ruled out: the merge decision, judging test results, anything on a keystroke path, vague options, and being the only record of a decision. Where it would go in this interface, if added: `Agents>agents` → a failure on a run offers `f`, which asks Mouse-1 one question with four options and writes the recommendation, the confidence and the options as a comment on the task. A person still decides. Expected cost of the first call after idle is 30 seconds, so `f` must show "asking, this can take half a minute" rather than appear to hang. ## Mouse-1, corrected Earlier notes in this file said "software is not installed". That was wrong: Mouse-1 is a **hosted API**, not a program. What exists here is `MOUSE_API_KEY`; what is missing is a client integration — an HTTP call like any other. No install is needed, and nothing has to run locally. The old project's policy still applies: triage only, never a gate, never a permit. ### Headroom: what the person has to do **Path A — the tool. Nothing to configure.** `headroom-ai` is installed for Pi on `.13`, `.27` and `.51`. To give it to one agent: 1. `Agents>agents` → `)` to the **extensions** tab. 2. `↑`/`↓` to `headroom-bridge`, press `space`. That writes a wrapper for that agent and sets its command; no other agent changes. 3. Run one task with that agent, then read the run log in `Agents>agents`: the tool call `compress_for_agent` appears with the token numbers before and after. **Path B — the provider. One file in the headroom container.** Headroom is started from `~/Docker/Containers/headroom/docker-compose.yml` with no config mount. Add one: ```yaml services: headroom: image: ghcr.io/chopratejas/headroom:latest container_name: headroom restart: always command: --port 8787 --no-telemetry ports: ['8787:8787'] volumes: - ./headroom-config.yaml:/app/config.yaml:ro environment: - LITELLM_CONFIG=/app/config.yaml ``` and a `headroom-config.yaml` beside it that teaches LiteLLM the router's models: ```yaml model_list: - model_name: deepseek/deepseek-v4-flash litellm_params: model: openai/deepseek-v4-flash api_base: http://192.168.20.13:20129/v1 api_key: os.environ/OMNI_KEY - model_name: auto/best-fast litellm_params: model: openai/auto/best-fast api_base: http://192.168.20.13:20129/v1 api_key: os.environ/OMNI_KEY ``` then restart the container. After that, add a provider in `~/.pi/agent/settings.json` pointing at `http://192.168.20.13:8787/v1`, and set one agent's model to `headroom/`. That is the path the earlier test was trying, and it fails today only because LiteLLM does not know those ids. **What the person does:** choose A or B. A needs no file edits. B needs the two files above and a container restart, and then one agent's model changed.