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snappy-agents

Switches your status bar to show every helper that's running.
description: "Triggers on prompt mention of 'snappy-agents'."
personal 2 files 10 recent evals

What it does for you

Switches your status bar to show every helper that's running.

What it produces

A recent result, so you can see the kind of work it returns.

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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-agents/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-agents.ts not present
code the skill can run
Optional. Many skills are just words and need no code at all.
Scripts
state/bin/snappy-agents/ not present
helper scripts
Optional. Added when a skill has a few commands to run.
Loader
state/skills/snappy-agents/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 · 2 deterministic · 2 judge

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
byline_view_file_exists
deterministic
The file 'state/log/byline-view.json' must exist after skill execution.
byline_view_content
deterministic
The 'state/log/byline-view.json' file must contain '{'view':'agents', ...}' and 'set_at' must be a valid ISO 8601 timestamp within the last 60 seconds.
statusline_output_agents_view
judge
The rendered output from 'bash $HOME/projects/snappy-os/state/bin/statusline.sh' must clearly indicate the agents-detail view (e.g., specific header line).
operator_notification
judge
The operator must be explicitly informed that the view is set, it auto-reverts in 5 minutes, and '/snappy-default' reverts sooner.

how it runs - the shared frame every skill uses 3/5 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
see `state/skills/snappy-agents/SKILL.md` Steps 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
present
fixes itself learns from gaps
When a run hits a gap, the skill gets edited on the spot [FIXED] or queued for a bigger rewrite [LOGGED], so it keeps getting better.
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 unknown 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. 5-min auto-revert is enforced by statusline.sh on every render — no cron

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
see `state/skills/snappy-agents/SKILL.md` Steps section
2 data
eval log
`state/log/evals.ndjson` (skill: "snappy-agents")

SKILL.md- the skill, written out in plain English

snappy-agents

One job: flip the byline from the default 1-line summary to a full per-agent detail view. Each row shows the agent's state (running / ok / late / broken / paused) + last-run age + a verb to fix the broken/late ones. Auto-reverts to default after 5 min.

Usage

/snappy-agents

No arguments. Single side effect: writes state/log/byline-view.json.

Steps

  1. Run:
   python3 -c "import json,datetime; open('$HOME/projects/snappy-os/state/log/byline-view.json','w').write(json.dumps({'view':'agents','set_at':datetime.datetime.now(datetime.UTC).strftime('%Y-%m-%dT%H:%M:%SZ')})+'\n')"
  1. Confirm by running bash $HOME/projects/snappy-os/state/bin/statusline.sh

and showing the operator the rendered output verbatim.

  1. Tell the operator:
  • the view is set
  • it auto-reverts in 5 min
  • to revert sooner: /snappy-default
  1. Log eval row to state/log/evals.ndjson:

{ts, skill:"snappy-agents", verb:"set-view", score: 1 if file written else 0}

Why

The default byline is two lines - fits the prompt strip but hides 90% of agent state. The TUI is too far to reach mid-conversation. Slash-command- flipped views are the middle ground: when the operator wants the full picture, one prompt expands it; when they're done, it auto-reverts so the byline doesn't camp.

Eval

Shape-gate:

  • state/log/byline-view.json exists with view: "agents" after invocation.
  • set_at parses as ISO timestamp within last 60s.
  • Statusline render contains the agents-detail header line.

Score = 1 if all three pass; else 0. Append to state/log/evals.ndjson with skill: "snappy-agents", verb: "set-view".

Gotchas

  • 5-min auto-revert is enforced by statusline.sh on every render - no cron

needed.

  • Multiple slash invocations within 5 min just refresh set_at; the view

doesn't toggle off. Use /snappy-default to clear before 5 min.

  • Future views (/snappy-loop, /snappy-skills, etc.) write the same file

with a different view: value. Adding a new view = one elif in state/bin/statusline.sh plus a sibling skill.

Rubric

criteria:
  - name: byline_view_file_exists
    kind: deterministic
    check: "The file 'state/log/byline-view.json' must exist after skill execution."
  - name: byline_view_content
    kind: deterministic
    check: "The 'state/log/byline-view.json' file must contain '{'view':'agents', ...}' and 'set_at' must be a valid ISO 8601 timestamp within the last 60 seconds."
  - name: statusline_output_agents_view
    kind: judge
    check: "The rendered output from 'bash $HOME/projects/snappy-os/state/bin/statusline.sh' must clearly indicate the agents-detail view (e.g., specific header line)."
  - name: operator_notification
    kind: judge
    check: "The operator must be explicitly informed that the view is set, it auto-reverts in 5 minutes, and '/snappy-default' reverts sooner."

AGENTS.md- what the AI loads when this skill comes up

snappy-agents - loader

Per-turn rules for the snappy-agents skill. Full reference: state/skills/snappy-agents/SKILL.md. Do not skip these.

Critical Rules

  • 5-min auto-revert is enforced by statusline.sh on every render - no cron

Commands

| ui dashboard | state/skills/snappy-agents/resources/ui.openui | |invoke: see state/skills/snappy-agents/SKILL.md Steps section |eval log: state/log/evals.ndjson (skill: "snappy-agents")

Self-Test

An agent reading this should correctly:

  1. [ ] Know which lib/bin artifact backs this skill (or that it is prose-only)
  2. [ ] Know what to write to state/log/evals.ndjson after invoking
  3. [ ] Know the eval mode (auto / shape / manual) from the .md frontmatter

Self-report

If this loader fell short, append a line:

echo "[$(date -u +%FT%TZ)] snappy-agents: <what was missing>" >> state/log/loader-feedback.log

<!-- kernel-ok: historical attribution for the PID-loader pattern. -->

Self-correcting loader (PID feedback)

This is the rule that makes loaders learn. Ported from snappy-kernel, where it demonstrably worked: the snappy-dom-cartographer skill mapped Skool admin UI once, every later ship-agent inherited the full map for free.

Before you finish, do two things:

1. Fix gaps (P - proportional). MANDATORY. If this loader didn't cover your case - if you had to read another file, run an undocumented command, work around a wrong selector, or discover a quirk - you MUST attempt an Edit to this AGENTS.md before you log.

  • Default action: edit this file. Surgical. Add the missing line, table

row, or code example where it belongs. No restructuring.

  • Only LOGGED is allowed when: the fix needs >10 lines, spans multiple

files, or requires a structural rewrite. In that case the state/regen/drain.sh queue picks it up asynchronously.

  • "I didn't have time" / "it's minor" / "the next agent will figure it out"

are NOT valid reasons. Minor gaps compound - that's the whole point of this loop.

  • Concrete example of a valid P-fix: discover agent-browser screenshot

takes path positionally not as --output <path>. One line in a table. Edit it in. Do not just log it.

  • The goal: the next agent never has to leave the loader.

2. Log the result.

echo "[$(date -u +%FT%TZ)] snappy-agents: <what was missing or fixed> [FIXED|LOGGED]" >> state/log/loader-feedback.log
  • FIXED = you patched this loader inline (P-fix).
  • LOGGED = too large for inline; the PostToolUse enqueue + Stop-hook drain

will rewrite the loader from scratch on next session-end.

Do not skip this. Every agent run must leave the system better than it found it. The loader is the setpoint; you are the sensor; the gap is the error signal; closing the gap is the correction.

OpenUI Resource

  • Skill-owned OpenUI Lang resource: state/skills/snappy-agents/resources/ui.openui. Read it before rendering or editing this skill's generated component surface.
  • Treat this resource as a first-class artifact of the skill, not a generic chat response. Improve it when the skill's user-facing output needs to become richer.
  • System resources compose OpenUI primitives and inherit SnappyChat tokens. Use ui_contract: branded in SKILL.md only for deliberate platform or client visuals.

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 mean 1.00 · 10 runs actor/auditor: unverifiable
deps none declared
timestamp verb score primary_issue artifact
2026-04-21 15:59Z - 1.00 - -
2026-04-21 03:53Z - 1.00 - -
2026-04-19 23:24Z - 1.00 - -
2026-04-21 15:59Z - 1.00 - -
2026-04-21 03:53Z - 1.00 - -
2026-04-19 23:24Z - 1.00 - -
2026-04-21 15:59Z - 1.00 - -
2026-04-21 03:53Z - 1.00 - -
2026-04-19 23:24Z - 1.00 - -
2026-04-21 03:53Z - 1.00 - -