Fleet Scorecard

Today is ${today}. Publish the daily fleet scorecard to memory/scorecard.md and append a trend row to memory/scorecard-history.csv.

The fleet is discovered at runtime, never hardcoded: it is this repo ("self") plus every non-archived entry in memory/instances.json (the registry fleet-control and spawn-instance maintain). With zero managed instances the scorecard simply covers the single self repo — still useful.

All data has already been gathered by scripts/prefetch-fleet-scorecard.sh (which ran outside the sandbox with network/gh access). You do not need network or gh — work only from the prefetched files below.

Voice

If soul/SOUL.md and soul/STYLE.md exist and are populated, read them and match the operator's voice in the notification (step 6). If they are empty templates or absent, use a clear, direct, neutral tone — terse, lowercase, no fluff.

Inputs (prefetched — read these)

• /tmp/fleet-scorecard/scorecard-body.md — the computed markdown tables (Fleet totals, Per-repo, Top skills by cost, Least reliable skills). These numbers are authoritative — do not recompute or alter them.
• /tmp/fleet-scorecard/metrics.json — today's key totals: total_runs, total_failures, generations, prompt_tokens, cached_tokens, completion_tokens, total_tokens, est_cost_usd, cache_discount_usd.

If /tmp/fleet-scorecard/scorecard-body.md is missing or empty, the prefetch failed or resolved an empty fleet — write a one-line note to /tmp/skill-result.txt saying so and stop (do not overwrite the existing scorecard, do not notify).

Steps

1. Load today's metrics and yesterday's baseline

• Read /tmp/fleet-scorecard/metrics.json (today).
• Read the last row of memory/scorecard-history.csv if it exists (the previous run's metrics) to compute deltas. If the file doesn't exist yet, this is the first run — deltas are "—".

2. Compute day-over-day deltas

For total_runs, total_failures, generations, total_tokens, est_cost_usd, cache_discount_usd, compute today − previous. Format as signed (e.g. +312 runs, +$148, +5 failures). These are cumulative all-time figures, so deltas show the last ~24h of activity.

3. Build the Alerts block

Scan the computed tables in scorecard-body.md and flag:

• Any skill in "Least reliable skills (last 14d)" with fail rate ≥ 25% (call it out by name + repo + rate). That table is already windowed to 14 days, so long-resolved incidents won't trigger false alarms — anything listed there is a current problem worth surfacing.
• Any cost spike: est_cost_usd delta > 1.5× the median daily delta from history (if ≥7 history rows exist), or just note the day's cost increase otherwise.
• If total_failures rose by more than 10 since yesterday, flag it.
• If no issues, write ✅ No anomalies — fleet healthy.

4. Write memory/scorecard.md

Structure (overwrite the file):

# 🛰️ Aeon Fleet Scorecard — as of ${today}

_Auto-generated daily by skills/fleet-scorecard. Tokens reported OpenRouter-style (cached_tokens ⊆ prompt_tokens)._

## Since last update (~24h)
| Metric | Δ |
|---|---:|
| Runs | <signed> |
| Failures | <signed> |
| Generations | <signed> |
| Total tokens | <signed, humanized> |
| Est. cost | <signed $> |
| Cache discount | <signed $> |

## Alerts
<the alerts block from step 3>

<PASTE the full contents of /tmp/fleet-scorecard/scorecard-body.md verbatim here>

---
_Sources: GitHub Actions run history + each repo's `memory/token-usage.csv`. Fleet resolved from memory/instances.json + self. Cost = Anthropic list price (estimate)._

5. Append the trend row

Append one line to memory/scorecard-history.csv (create with a header if it doesn't exist):

date,total_runs,total_failures,generations,prompt_tokens,cached_tokens,completion_tokens,total_tokens,est_cost_usd,cache_discount_usd

Use ${today} for the date and the values straight from metrics.json. Append, never rewrite prior rows.

6. Notify

Write a terse daily pulse to /tmp/scorecard-notify.md and send it with ./notify -f /tmp/scorecard-notify.md. One short paragraph — today's totals (runs, est. cost, total tokens), the headline deltas, and any alert. Example shape: "fleet at 12.5k runs, ~$7.8k notional. +312 runs / +$148 since yesterday. cost-report still failing (88% fail). caching saved ~$43k." Also copy this text to /tmp/skill-result.txt so the framework captures it.

7. Memory log

Append a one-line entry to memory/logs/${today}.md noting the scorecard ran and the headline numbers (so future skills like self-review/reflect see it).

Notes

• Numbers come only from the prefetched files — never invent or estimate figures yourself.
• The scorecard is cumulative/all-time; the deltas are what make the daily run useful.
• GitHub Actions retains runs ~90 days, so the run history is a rolling window; the token CSVs are the durable record committed in each repo.

Sandbox Note

This skill needs no network inside the sandbox — all gh/API work happens in scripts/prefetch-fleet-scorecard.sh, which runs in the workflow's prefetch phase with gh auth. If the prefetch's cross-repo reads fail for a managed instance, it's almost always the GitHub token scope (the token needs read access to that instance's repo; self is always readable). The prefetch degrades gracefully — a repo it can't read is simply absent from the tables rather than crashing the run.

Required Env Vars

None for the skill itself. scripts/prefetch-fleet-scorecard.sh uses GH_TOKEN/GITHUB_TOKEN (provided by the workflow) and reads GITHUB_REPOSITORY to resolve "self".

Output

End with a ## Summary listing the files written (memory/scorecard.md, memory/scorecard-history.csv, the log entry) and any alerts raised.