.md file to compare - side-by-side diff against bug-triage
bug-triage
description: "Triggers on prompt mention of 'bug-triage'."
What it does for you
Gathers reported problems and ranks them so you fix what matters first.
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.
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/bug-triage/SKILL.md
present
state/lib/bug-triage.ts
not present
state/bin/bug-triage/
not present
state/skills/bug-triage/AGENTS.md
present
how it's graded - what counts as a good run 5 criteria · 4 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.
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 - NEVER hard-fail when gh is unauthenticated - log the auth failure and continue with the other two sources (sweep + Xano)
- ALWAYS cluster by exact stack-fingerprint FIRST, then fall back to fuzzy keyword Jaccard ≥ 0.4 - not the other way around
- ALWAYS rank clusters by size × recency, not size alone - old loud bugs shouldn't drown out fresh ones
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
collect sweep snapshot + `gh issue list --state=open` + Xano error-log, normalize, cluster, write `state/log/bug-triage/<date>.md`
`clusters_are_unique` (no two clusters share the same fingerprint) AND shape gate
SKILL.md- the skill, written out in plain English
Backed by: state/lib/sweep.ts + state/lib/xano.ts
bug-triage
Reads sweep snapshot (filtering to items matching bug keywords), gh issue list --state=open across active repos, and Xano error-log rows from the last N days. Clusters by stack-trace fingerprint or keyword overlap.
Steps
- Collect the three sources in parallel.
- Normalize to
{source, ref, text, ts, repo?}. - Cluster: exact-match on stack fingerprint first, then fuzzy on
keyword Jaccard ≥ 0.4.
- Rank clusters by
size × recency. - Emit
state/log/bug-triage/<date>.md.
Eval
score("bug-triage", run_id, {
score:
shape_ok && clusters_are_unique ? 1.0 :
shape_ok ? 0.5 :
0.0,
total_signals: total,
cluster_count: clusters.length,
unclustered: unclustered.length,
primary_issue:
!shape_ok ? "shape-failed" :
unclustered.length > total * 0.5 ? "clustering-threshold-too-tight" :
null,
});
clusters_are_unique: no two clusters share the same fingerprint. Shape gate prevents silent clustering failure.
Gotchas
ghmust be authenticated; if not, log the auth failure and continue
with the other two sources rather than hard-failing.
- Jaccard threshold 0.4 is a guess; tune once we have a week of data.
Rubric
criteria:
- name: output_file_created
kind: deterministic
check: "File 'state/log/bug-triage/<date>.md' exists and is non-empty (file size > 100 bytes)."
- name: clusters_nonzero
kind: deterministic
check: "Clusters array has length > 0 (at least one cluster identified; not empty array)."
- name: cluster_uniqueness
kind: deterministic
check: "clusters_are_unique = true; no two clusters share the same stack fingerprint."
- name: signal_count_threshold
kind: deterministic
check: "total_signals ≥ 1 (at least one signal collected from sweep, GitHub, or Xano)."
- name: cluster_quality
kind: judge
check: "Clusters are semantically cohesive (signals within a cluster share root cause); unclustered < total * 0.5; data sources are properly integrated."AGENTS.md- what the AI loads when this skill comes up
bug-triage - loader
Per-turn rules for the bug-triage skill. Full reference: state/skills/bug-triage/SKILL.md. Do not skip these.
Critical Rules
- NEVER hard-fail when
ghis unauthenticated - log the auth failure and continue with the other two sources (sweep + Xano) - ALWAYS cluster by exact stack-fingerprint FIRST, then fall back to fuzzy keyword Jaccard ≥ 0.4 - not the other way around
- ALWAYS rank clusters by
size × recency, not size alone - old loud bugs shouldn't drown out fresh ones
Commands
| ui model | live composition via compose_inline, persisted as artifact lang_body, reopened with OpenArtifact | |invoke: collect sweep snapshot + gh issue list --state=open + Xano error-log, normalize, cluster, write state/log/bug-triage/<date>.md |verify: clusters_are_unique (no two clusters share the same fingerprint) AND shape gate |eval log: state/log/evals.ndjson (skill: "bug-triage")
Known Pitfalls
- Jaccard threshold 0.4 is a guess. Tune once a week of data exists. If
unclustered.length > total * 0.5, primary_issue isclustering-threshold-too-tight. shape_okis the floor - score 0.5 if shape passes but uniqueness fails; 0.0 if shape itself fails.
Self-Test
An agent reading this should correctly:
- [ ] Continue triage when
gh authis missing (log + proceed) - [ ] Cluster by stack-fingerprint before keyword Jaccard
- [ ] Flag
unclustered > 50%as a tuning issue, not a failure
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