Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add WinterDDo/claude-code-skill-autopilot --skill profilegit clone --depth 1 https://github.com/WinterDDo/claude-code-skill-autopilotWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/winterddo/claude-code-skill-autopilot/profile)<a href="https://agentmods.dev/skills/winterddo/claude-code-skill-autopilot/profile"><img src="https://agentmods.dev/badge/skills/winterddo/claude-code-skill-autopilot/profile/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/winterddo/claude-code-skill-autopilot/profile"><img src="https://agentmods.dev/badge/skills/winterddo/claude-code-skill-autopilot/profile.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00079 | $0.00477 |
| Opus 5.5 | $0.00032 | $0.00191 |
| Sonnet 5.5 | $0.00016 | $0.00095 |
| Haiku 4.5 | $0.00008 | $0.00048 |
Grade A, and why
profile scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Autopilot dashboard
Every number MUST be traceable to a real entry in the data files. Never fabricate or extrapolate a value claim. If a number is zero, show zero.
Data sources
Read from ~/.claude/command-autopilot/: state.json (counters, milestones, config), events.jsonl + events-archive.jsonl (the ledger), learned.json (rules), skills-index.json.
Report (user's language, compact)
- Value ledger — counts from events: auto plan-mode entries, skills auto-invoked (top 3 by count, with names), suggestions accepted vs made. One line each, with the period covered.
- Before/after — compare the oldest 7 days of events against the newest 7 (only if ≥14 days of data; otherwise say "still collecting"): self-used commands per week then vs now. This is the user's own growth, shown from their own data.
- Learned rules — each in_force rule with its evidence count and last-confirmed date. If none: "still observing, first rules typically appear after ~10 sessions."
- Mastered — habits with self-use evidence; note that teaching for them has naturally stopped.
- Controls — one line: config skill to quiet/mute, evolve skill to re-distill, "delete rule N" works right here.
Feedback draft
If the user is dissatisfied with any suggestion behavior, offer to draft a GitHub issue for WinterDDo/claude-code-skill-autopilot: title, what happened, expected behavior, and (only with explicit consent) the relevant anonymized evidence lines. Show the draft; the user files it themselves.
Rule deletion
"Delete rule N" → remove it from learned.json, confirm in one line.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 26 lines · 79 tokens per session scan A f6eba13482e7
profile is a skill published in the GitHub repository WinterDDo/claude-code-skill-autopilot (6 stars, last pushed 4mo ago), licensed MIT. It adds 79 tokens to every session and 477 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
skill-iterative-loop
Run tasks in a loop until goals are met — use for iterative refinement, polling, or convergence.
sys-configure
Configure Claude Octopus — redirects to /octo:setup interactive wizard.
alive:system-cleanup
The world feels messy. Stale tasks, orphan folders, v2 remnants, unsaved sessions — entropy is accumulating and needs to be addressed before it compounds. Scans across all walnuts, then surfaces issues one at a time.
alive:world
The human doesn't know what to work on, or wants to see everything at once. They need the big picture — what's active, what's stale, what needs attention. Renders a live world view grouped by ALIVE domain, then routes to open, tidy, find, history, or map.
alive:bundle
Create, share, and graduate bundles — the unit of focused work within a walnut. Manages the full bundle lifecycle from creation through sharing to graduation.
alive:settings
The human wants to adjust how the system behaves — not what it contains, but how it feels. Voice, rhythm, preferences, walnut-level config, full permissions toggleable, named squirrel config, action logging toggle. The system adapting to them. Routes to preferences.yaml or walnut config.yaml depending on scope. For…