bash ~/projects/snappy-os/state/bin/agents/list. .md file to compare - side-by-side diff against snappy-list
snappy-list
What it does for you
Lists every helper running now, with how long each has been going.
What it produces
A recent result, so you can see the kind of work it returns.
loading…
How to get it
These run inside the Snappy workspace. Want this working in your business? I set skills like this up with you, in one focused week.
For developers how this skill is built, graded, and how it runs
at a glance- the short version
what's inside - the parts that make up a skill 2/4 present
A skill is just a few plain-text files. Only the main one is required. The rest are optional, added as the work needs them. This is what the skill is made of; how it runs is just below.
state/skills/snappy-list/SKILL.md
present
state/lib/snappy-list.ts
not present
state/bin/snappy-list/
not present
state/skills/snappy-list/AGENTS.md
present
how it's graded - what counts as a good run 4 criteria · 4 deterministic
Each row is one thing a good run has to get right. deterministic means a quick check decides, pass or fail. judge means the AI reads the result and rates it. Grading each piece on its own (instead of one overall score) shows exactly where a run fell short, so the fix is obvious.
how it runs - the shared frame every skill uses 2/5 present
Every skill runs the same way. One part does the work, a separate part checks it, and a short loader hands the AI exactly what it needs for the job. Anything this skill doesn't use shows a one-line note saying why, on purpose, not by accident.
This skill doesn't fix its own gaps yet.
state/log/evals.ndjson - /snappy-list lists running BACKGROUND AGENTS, not skills. If the user is asking for the skill catalog, route to state/index.md (or find-skills for fuzzy lookup). The agent inventory is state/agents/.json; the skill catalog is state/skills//. (writeback 2026-04-28T22:33:27Z - loader did not match user intent who asked for skills.)
- Agents are scoped to this machine. An agent started on the Mac mini does NOT appear in /snappy-list on the MBP and vice versa. The cross-machine inventory is the Ops view (TUI, press 4); this skill is the local view only.
- status: stopped agents are deleted immediately - they will not appear in the list. Use state/log/agents.ndjson for history.
- normalizeId() strips any character outside [a-z0-9-]. Caller passing Verify Loop! ends up at on-disk id verify-loop. Cite the canonical id in any pause/resume/stop command.
- The invoking agent (NOT list.sh - it's a thin wrapper) appends one eval row via score() with actor_session_id ≠ auditor_session_id (CONSTITUTION invariants #3 + #4).
what it has learned - fixes written back in over time sample
When a run hits something this skill didn't handle, the fix gets written back into the skill so it doesn't happen again. FIXED means it was corrected on the spot. LOGGED means it's queued for a bigger rewrite. Either way, the skill gets a little better and never makes the same mistake twice.
- Loading feedback rows…
how the work flows- step by step
`bash ~/projects/snappy-os/state/bin/agents/list.sh` (prints JSON; one row per agent)
SKILL.md- the skill, written out in plain English
snappy-list
One job: answer "what background agents do I have running right now, on this machine?" This skill is the full runtime agent inventory.
Usage
/snappy-list
No argument. Reads state/agents/*.json and prints one line per agent.
Steps
- Run:
bash ~/projects/snappy-os/state/bin/agents/list.sh
- Parse the JSON on stdout. For each agent, show:
id(e.g.default,verify-loop)status(running / paused / stopped / done)ticks/max_tickslast_tick_atas relative age (e.g.4m ago,-)- the first 60 chars of
prompt
- If none are running, say so in one line and exit - don't offer to
invent work.
- If any agent is running, optionally call AskUserQuestion with one
question per agent offering Pause / Resume / Stop / Leave running. Apply the picks via ctl.ts pause|resume|stop <id>. Skip the picker if the user's message was purely informational.
- The invoking agent (not list.sh - it's a thin wrapper) appends one
eval row via score() with {skill:"snappy-list", verb:"list", score: 1 if list-printed else 0}, supplying its own actor_session_id and a separate auditor_session_id (CONSTITUTION invariant #4 + #3).
Why
state/directive.json was one file → one agent. After Commit 4 the system runs N named agents from state/agents/<id>.json. This skill is the full inventory view.
Also the one place where the user can pause/stop individual agents without guessing at paths.
Eval
Shape-gate:
state/agents/was scanned (or "no agents running" was reported).- Every agent row that was present on disk appeared in the output.
- An eval row was appended.
Score = 1 if shape passes else 0.
Gotchas
- Agents are scoped to this machine. An agent started on the Mac Mini
does NOT appear in /snappy-list on the MBP (and vice versa). The Ops view (TUI, press 4) is the cross-machine inventory; this skill is the local one.
status: stoppedagents are deleted immediately; they won't show in
the list. Use state/log/agents.ndjson for history.
normalizeId()strips any character outside[a-z0-9-]. If a caller
passed Verify Loop!, the on-disk id is verify-loop.
Rubric
criteria:
- name: agent_count_nonzero_or_none
kind: deterministic
check: "Either state/agents/*.json has ≥ 1 agent (at least one file exists) OR script reports 'no agents running'. Not silently empty."
- name: all_agents_in_output
kind: deterministic
check: "Every agent file on disk appears in output as a row. If 3 agents exist in state/agents/, all 3 are listed (not truncated)."
- name: agent_metadata_accurate
kind: deterministic
check: "Per-agent row shows id, status (running|paused|stopped|done), ticks/max_ticks, last_tick_at, first 60 chars of prompt. Values match on-disk JSON."
- name: eval_row_written
kind: deterministic
check: "state/log/evals.ndjson receives row with skill='snappy-list', verb='list', score=1 if all agents listed, score=0 if empty/incomplete."AGENTS.md- what the AI loads when this skill comes up
snappy-list - loader
Per-turn rules for the snappy-list skill. Full reference: state/skills/snappy-list/SKILL.md. Do not skip these.
Critical Rules
/snappy-listlists running BACKGROUND AGENTS, not skills. If the user is asking for the skill catalog, route tostate/index.md(orfind-skillsfor fuzzy lookup). The agent inventory isstate/agents/*.json; the skill catalog isstate/skills/*/. (writeback 2026-04-28T22:33:27Z - loader did not match user intent who asked for skills.)- **Agents are scoped to this machine.** An agent started on the Mac mini does NOT appear in
/snappy-liston the MBP and vice versa. The cross-machine inventory is the Ops view (TUI, press4); this skill is the local view only. status: stoppedagents are deleted immediately - they will not appear in the list. Usestate/log/agents.ndjsonfor history.normalizeId()strips any character outside[a-z0-9-]. Caller passingVerify Loop!ends up at on-disk idverify-loop. Cite the canonical id in any pause/resume/stop command.- The invoking agent (NOT
list.sh- it's a thin wrapper) appends one eval row viascore()withactor_session_id ≠ auditor_session_id(CONSTITUTION invariants #3 + #4).
Commands
| ui model | live composition via compose_inline, persisted as artifact lang_body, reopened with OpenArtifact | |invoke: bash ~/projects/snappy-os/state/bin/agents/list.sh (prints JSON; one row per agent) |control after listing: npx tsx state/bin/agents/ctl.ts {pause|resume|stop} <id> (id = normalized slug) |history (cross-machine): state/log/agents.ndjson |catalog of SKILLS (different surface): state/index.md or npx skills find <kw> |eval log: state/log/evals.ndjson (skill: "snappy-list", eval_mode: auto-shape; shape gate: list printed OR "no agents running" line)
Self-Test
An agent reading this should correctly:
- [ ] Distinguish "list agents" (this skill, reads
state/agents/) from "list skills" (route tostate/index.md) - [ ] Treat
state/agents/as machine-local - never claim cross-machine inventory - [ ] Use
normalizeId()'s canonical slug when piping to ctl.ts pause/resume/stop - [ ] Append exactly one eval row per invocation with actor ≠ auditor
Found a gap? Edit this file. <!-- footer-injection-point -->
api.ts- the code it can call
⚠ no api.ts - this skill has no typed action surface
scripts- helper scripts it can run
prose-only skill - 2 inline code blocks live in SKILL.md above (no state/bin/ sidecar yet).
how we check it- the checks, plus the last 10 runs
no recent runs logged - the eval contract is declared but nothing has been graded yet