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krisp-inbox

Reads your latest meetings and surfaces follow-ups waiting on you.
description: "Triggers on prompt mention of 'krisp-inbox'."
personal 2 files 10 recent evals

What it does for you

Reads your latest meetings and surfaces follow-ups waiting on you.

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
categoryKnowledge
stages2
dependskrisp

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/krisp-inbox.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/krisp-inbox.ts not present
code the skill can run
Optional. Many skills are just words and need no code at all.
Scripts
state/bin/krisp-inbox/ not present
helper scripts
Optional. Added when a skill has a few commands to run.
Loader
state/skills/krisp-inbox.agents.md present
what the AI loads on the fly
Loaded automatically the moment this skill is needed. Kept short on purpose.

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
skill is prose, 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
not present

No separate check found. Without one, the part that makes the work could end up approving its own work, worth a closer look.

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. ALWAYS dedup against ray-todo for the same date — krisp-inbox covers follow-ups that never became commitments, ray-todo covers commitments; overlap must be reported (even as 0)
  2. ALWAYS write the dedup count to the output file — the shape gate's dedup_run check requires explicit overlap mention
  3. ALWAYS use ~/.claude/cache/krisp/meetings.json — Krisp is the one documented MCP exception in program.md "Don't list", isolated to this daily cron dump
  4. NEVER skip writing the file — score 0.0 if no state/log/krisp-inbox/<date>.md is produced

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 krisp
1 generator
invoke
skill is prose, runs the steps in `state/skills/krisp-inbox.md` (read cache → dispatch gemini per meeting → dedup → write)
2 data
eval log
`state/log/evals.ndjson` (skill: "krisp-inbox")

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

Backed by: state/lib/log.ts (reads ~/.claude/cache/krisp/ dump) + state/lib/eval.ts (writes the score row)

krisp-inbox

Reads ~/.claude/cache/krisp/meetings.json, groups by participant, and emits a "who's waiting on what" summary. Complement to ray-todo (which covers commitments); this covers follow-ups that never became commitments.

Steps

  1. Read meetings cache (refresh if stale).
  2. For each meeting, dispatch gemini with transcript (if available) +

prompt "list follow-ups Robert owes the other participant."

  1. Dedupe against ray-todo output for the same date.
  2. Write to state/log/krisp-inbox/<date>.md.

Eval

Auto. Shape gate on the produced summary file:

CheckRequiredWhat it verifies
file_writtenyesstate/log/krisp-inbox/<date>.md exists and is non-empty
has_followupsyesBody contains at least one - [ ] checkbox row OR an explicit "no follow-ups" sentinel
dedup_runyesOutput mentions ray-todo overlap count (even if 0) - proves the dedup pass executed

Score 1.0 if all three pass, 0.5 if file written but missing dedup line, 0.0 if no file. Eval row written via state/lib/eval.ts.

Graduation

Prose; no script until the dedup logic is stable.

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

krisp-inbox - loader

Per-turn rules for the krisp-inbox skill. Full reference: state/skills/krisp-inbox.md. Do not skip these.

Critical Rules

  • ALWAYS dedup against ray-todo for the same date - krisp-inbox covers follow-ups that never became commitments, ray-todo covers commitments; overlap must be reported (even as 0)
  • ALWAYS write the dedup count to the output file - the shape gate's dedup_run check requires explicit overlap mention
  • ALWAYS use ~/.claude/cache/krisp/meetings.json - Krisp is the one documented MCP exception in program.md "Don't list", isolated to this daily cron dump
  • NEVER skip writing the file - score 0.0 if no state/log/krisp-inbox/<date>.md is produced

Commands

|invoke: skill is prose, runs the steps in state/skills/krisp-inbox.md (read cache → dispatch gemini per meeting → dedup → write) |cache refresh: bash state/bin/krisp/refresh.sh (cron-driven dump) |eval log: state/log/evals.ndjson (skill: "krisp-inbox")

Known Pitfalls

  • Cache may be stale if krisp/refresh.sh cron didn't run - refresh before scoring rather than emitting an empty inbox
  • Output must contain at least one - [ ] checkbox row OR an explicit "no follow-ups" sentinel - silent empty fails the has_followups shape check

Self-Test

An agent reading this should correctly:

  1. [ ] Cite the ray-todo overlap count in the output file even when the count is 0?
  2. [ ] Read the Krisp cache from ~/.claude/cache/krisp/meetings.json?
  3. [ ] Score 0.5 if file written but dedup line missing, 1.0 if all three shape checks pass?

Self-report

If this loader fell short, append a line:

echo "[$(date -u +%FT%TZ)] krisp-inbox: <what was missing>" >> ~/.claude/logs/snappy-os-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)] <skill-name>: <what was missing or fixed> [FIXED|LOGGED]" >> state/log/agents-md-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 - no sidecar under state/bin/ yet. Steps, if any, are described in SKILL.md.

how we check it- the checks, plus the last 10 runs

rubric auto no rubric declared
recent mean 1.00 · 10 runs actor/auditor: unverifiable
deps krisp
timestamp verb score primary_issue artifact
2026-04-26 04:55Z - 1.00 - -
2026-04-26 04:26Z - 1.00 - -
2026-04-25 04:11Z - 1.00 - -
2026-04-21 15:58Z - 1.00 - -
2026-04-21 15:56Z - 1.00 - -
2026-04-21 03:53Z - 1.00 - -
2026-04-26 04:55Z - 1.00 - -
2026-04-26 04:26Z - 1.00 - -
2026-04-25 04:11Z - 1.00 - -
2026-04-21 15:58Z - 1.00 - -