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snappy-list

Lists every helper running now, with how long each has been going.
personal 2 files

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.

Work with me
For developers how this skill is built, graded, and how it runs

at a glance- the short version

eval modeauto-shape
categoryOps
stages2

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.

The skill
state/skills/snappy-list/SKILL.md present
the skill itself, in plain text
The main file. It says what the skill is and lays out the steps in plain English.
Code
state/lib/snappy-list.ts not present
code the skill can run
Optional. Many skills are just words and need no code at all.
Scripts
state/bin/snappy-list/ not present
helper scripts
Optional. Added when a skill has a few commands to run.
Loader
state/skills/snappy-list/AGENTS.md present
what the AI loads on the fly
Loaded automatically the moment this skill is needed. Kept short on purpose.

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.

name
kind
check
agent_count_nonzero_or_none
deterministic
Either state/agents/*.json has ≥ 1 agent (at least one file exists) OR script reports 'no agents running'. Not silently empty.
all_agents_in_output
deterministic
Every agent file on disk appears in output as a row. If 3 agents exist in state/agents/, all 3 are listed (not truncated).
agent_metadata_accurate
deterministic
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.
eval_row_written
deterministic
state/log/evals.ndjson receives row with skill='snappy-list', verb='list', score=1 if all agents listed, score=0 if empty/incomplete.

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.

makes the work The worker
inferred
bash ~/projects/snappy-os/state/bin/agents/list. from the run command
No worker is named directly, so the command this skill runs is treated as the worker.
checks the work The reviewer
inferred
shape gate an automatic check
The check is an automatic pass or fail on the shape of the result, run separately from the work itself.
frame
learns Self-correction
not present

This skill doesn't fix its own gaps yet.

tidies up Background fixes
present
queued for rewrite runs in the background
Bigger fixes that can't be made on the spot get queued and rewritten in the background later.
remembers Run history
present
state/log/evals.ndjson auto-shape runs
Every run is written down here, so the next time this skill is used it already knows how the last runs went.
Critical rules the things this skill must not get wrong
  1. /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.)
  2. 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.
  3. status: stopped agents are deleted immediately - they will not appear in the list. Use state/log/agents.ndjson for history.
  4. 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.
  5. 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.

  1. Loading feedback rows…

how the work flows- step by step

1 generator
invoke
`bash ~/projects/snappy-os/state/bin/agents/list.sh` (prints JSON; one row per agent)
2 data
eval log
`state/log/evals.ndjson` (skill: "snappy-list", eval_mode: auto-shape; shape gate: list printed OR "no agents running" line)

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

  1. Run:
   bash ~/projects/snappy-os/state/bin/agents/list.sh
  1. Parse the JSON on stdout. For each agent, show:
  • id (e.g. default, verify-loop)
  • status (running / paused / stopped / done)
  • ticks/max_ticks
  • last_tick_at as relative age (e.g. 4m ago, - )
  • the first 60 chars of prompt
  1. If none are running, say so in one line and exit - don't offer to

invent work.

  1. 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.

  1. 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: stopped agents 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-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).

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:

  1. [ ] Distinguish "list agents" (this skill, reads state/agents/) from "list skills" (route to state/index.md)
  2. [ ] Treat state/agents/ as machine-local - never claim cross-machine inventory
  3. [ ] Use normalizeId()'s canonical slug when piping to ctl.ts pause/resume/stop
  4. [ ] 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

rubric auto-shape no rubric declared
recent no runs actor/auditor: unverifiable
deps none declared

no recent runs logged - the eval contract is declared but nothing has been graded yet