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dormant-ping

Spots clients you've gone quiet with and drafts a check-in for your approval.
description: "Triggers on prompt mention of 'dormant-ping'."
personal 2 files 10 recent evals

What it does for you

Spots clients you've gone quiet with and drafts a check-in for your approval.

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
categoryClients
stages3
dependsclients

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/dormant-ping/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/dormant-ping.ts not present
code the skill can run
Optional. Many skills are just words and need no code at all.
Scripts
state/bin/dormant-ping/ not present
helper scripts
Optional. Added when a skill has a few commands to run.
Loader
state/skills/dormant-ping/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 · 3 deterministic · 1 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
draft_files_written_correctly
deterministic
For each client meeting the threshold, a markdown file is written to 'state/log/dormant-ping/<date>/<slug>.md' with the DM draft.
never_auto_sent
deterministic
The run log for this skill ('state/log/dormant-ping/<date>/<run_id>.log') must contain zero instances of 'action: \"deliver\"'.
tone_check_passed_for_all
deterministic
The evaluation score for this skill must report 'tone_violations_total: 0'.
client_filters_correct
judge
The skill output appropriately filters clients based on 'dormant_risk ≥ threshold_days' and respects per-client thresholds from 'sources/clients/<slug>.md' if present.

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
prose skill — 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
grep '"action":"deliver"'` over from the check command
The check is a quick command that confirms the result looks right.
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 auto 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. NEVER auto-send. The skill writes drafts to state/log/dormant-ping/<date>/<slug>.md and stops. The never_sent invariant is verified by lint greppping for action: "deliver" rows (must be zero). Sending is a separate explicit skill.
  2. ALWAYS run every draft through voice.checkTone() before writing. A "checking in" draft is exactly the kind of copy that sprouts hype words ("quick hello, just wanted to supercharge our cadence") — the gate catches it.
  3. NEVER use scarcity framing ("idle hours", "leftover budget"). Value-first only. (feedback_no_scarcity_offers.md)
  4. NEVER open with personal stories ("I was…", "Last week I…"). Technical reports only. (feedback_no_personal_stories.md)

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

inputs clients
1 generator
invoke
prose skill — read latest `client-pulse` output → filter dormant_days ≥ threshold → dispatch gemini per client → checkTone → write draft
2 auditor
verify
`grep '"action":"deliver"'` over `state/log/chain.ndjson` for this skill's run_id must return zero
3 data
eval log
`state/log/evals.ndjson` (auto eval — skill: "dormant-ping")

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

Backed by: state/lib/knowledge.ts + state/lib/email.ts (draft only)

dormant-ping

Reads client-pulse output, filters to dormant_risk ≥ threshold_days, drafts a DM candidate per client via dispatch. Hard gate: writes to state/log/dormant-ping/<date>/<slug>.md and stops. Sending is a separate explicit skill.

Steps

  1. Read latest client-pulse output (invoke if stale).
  2. Filter by dormant_days ≥ threshold.
  3. For each, dispatch gemini with {client_context, last_touch_excerpt}

→ DM draft.

  1. Run every draft through voice.checkTone() before writing.
  2. Write drafts; log chain row; exit.

Eval

Deterministic, three-part:

score("dormant-ping", run_id, {
  score:
    shape_ok && never_sent && all_drafts_pass_tone ? 1.0 :
    shape_ok && never_sent ? 0.5 :
    0.0,
  drafts_written: drafts.length,
  tone_violations_total: sum(drafts.map(d => d.violations.length)),
  primary_issue:
    !never_sent ? "auto-send-attempted" :
    !all_drafts_pass_tone ? "voice-gate-failed" :
    null,
});

The never_sent invariant - no send fn is imported, no HTTP POST happens - is verified by a lint check that greps this skill's run log for action: "deliver" rows (must be zero).

Gotchas

  • voice.checkTone() gate is load-bearing. A "checking in" draft is

exactly the kind of copy that sprouts hype words ("quick hello, just wanted to supercharge our cadence") - the gate catches it.

  • Threshold is per-client, not global. Read from

sources/clients/<slug>.md if present.

Rubric

criteria:
  - name: draft_files_written_correctly
    kind: deterministic
    check: "For each client meeting the threshold, a markdown file is written to 'state/log/dormant-ping/<date>/<slug>.md' with the DM draft."
  - name: never_auto_sent
    kind: deterministic
    check: "The run log for this skill ('state/log/dormant-ping/<date>/<run_id>.log') must contain zero instances of 'action: \"deliver\"'."
  - name: tone_check_passed_for_all
    kind: deterministic
    check: "The evaluation score for this skill must report 'tone_violations_total: 0'."
  - name: client_filters_correct
    kind: judge
    check: "The skill output appropriately filters clients based on 'dormant_risk ≥ threshold_days' and respects per-client thresholds from 'sources/clients/<slug>.md' if present."

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

dormant-ping - loader

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

Critical Rules

  • NEVER auto-send. The skill writes drafts to state/log/dormant-ping/<date>/<slug>.md and stops. The never_sent invariant is verified by lint greppping for action: "deliver" rows (must be zero). Sending is a separate explicit skill.
  • ALWAYS run every draft through voice.checkTone() before writing. A "checking in" draft is exactly the kind of copy that sprouts hype words ("quick hello, just wanted to supercharge our cadence") - the gate catches it.
  • NEVER use scarcity framing ("idle hours", "leftover budget"). Value-first only. (feedback_no_scarcity_offers.md)
  • NEVER open with personal stories ("I was…", "Last week I…"). Technical reports only. (feedback_no_personal_stories.md)

Commands

| ui dashboard | state/skills/dormant-ping/resources/ui.openui | |invoke: prose skill - read latest client-pulse output → filter dormant_days ≥ threshold → dispatch gemini per client → checkTone → write draft |verify: grep '"action":"deliver"' over state/log/chain.ndjson for this skill's run_id must return zero |eval log: state/log/evals.ndjson (auto eval - skill: "dormant-ping")

OpenUI Resource

  • Skill-owned OpenUI Lang resource: state/skills/dormant-ping/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.

Known Pitfalls

  • Threshold is per-client, not global. Read from sources/clients/<slug>.md if present.
  • Score is three-part: shape_ok && never_sent && all_drafts_pass_tone → 1.0; missing tone-pass → 0.5; missing never-sent (auto-send attempted) → 0.0

Self-Test

An agent reading this should correctly:

  1. [ ] Refuse to import any send fn into this skill's run path
  2. [ ] Apply voice.checkTone() to every draft before write
  3. [ ] Read per-client threshold from sources/clients/<slug>.md, not a global default

Self-report

If this loader fell short, append a line:

echo "[$(date -u +%FT%TZ)] dormant-ping: <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)] dormant-ping: <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.

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 + never-auto-sent + content-polish pass
recent mean 1.00 · 10 runs actor/auditor: unverifiable
deps clients
timestamp verb score primary_issue artifact
2026-04-25 04:11Z - 1.00 - -
2026-04-21 15:59Z - 1.00 - -
2026-04-21 15:56Z - 1.00 - -
2026-04-21 03:53Z - 1.00 - -
2026-04-25 04:11Z - 1.00 - -
2026-04-21 15:59Z - 1.00 - -
2026-04-21 15:56Z - 1.00 - -
2026-04-21 03:53Z - 1.00 - -
2026-04-25 04:11Z - 1.00 - -
2026-04-21 15:59Z - 1.00 - -