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 anhe2021212-spec/Turritopsis --skill turritopsis-onboardinggit clone --depth 1 https://github.com/anhe2021212-spec/TurritopsisWrote 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/anhe2021212-spec/turritopsis/turritopsis-onboarding)<a href="https://agentmods.dev/skills/anhe2021212-spec/turritopsis/turritopsis-onboarding"><img src="https://agentmods.dev/badge/skills/anhe2021212-spec/turritopsis/turritopsis-onboarding/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/anhe2021212-spec/turritopsis/turritopsis-onboarding"><img src="https://agentmods.dev/badge/skills/anhe2021212-spec/turritopsis/turritopsis-onboarding.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 | $0.00077 | $0.00821 |
| Opus 5 | $0.00039 | $0.00411 |
| Sonnet 5 | $0.00015 | $0.00164 |
| Haiku 4.5 | $0.00008 | $0.00082 |
Grade A, and why
turritopsis-onboarding 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Turritopsis Onboarding
Use the installed Agent as the classifier and writer. Keep scanning local and deterministic; never require a second model or API key for onboarding.
Cold start
- Run
turritopsis scan. Reuse existingscan-evidence.jsonunless the repository changed enough to justify--refresh. - Read
scan-run.jsonfirst, then inspect coverage and omitted materials inscan-evidence.json. Do not assume the snapshot contains everything. - Read stage-types.md. Select one responsibility for each Stage.
- Read project-suites.md. Choose the smallest suitable suite; combine suites for hybrids.
- Inspect only the evidence needed to classify durable knowledge regions. Do not generate one Stage per file, directory, or document.
- Read cli-contract.md, then write
skeleton.jsonfrom that public contract. Never inspect installed package source to discover fields, revisions, or write calls. - Run
turritopsis apply-skeleton skeleton.json. Fix every validation error instead of bypassing it. - Run
turritopsis get-stage --all, write the Stage body files and one batch manifest, then useturritopsis update-stages --manifest updates.json --actor <name>.
Use paired-examples.md when a Stage is structurally valid but vague. Use the seven fixtures when selecting a suite:
- fixture-web-saas.json
- fixture-library-sdk.json
- fixture-data-ml.json
- fixture-mobile-desktop.json
- fixture-infrastructure.json
- fixture-embedded-iot.json
- fixture-research-protocol.json
Fixtures are examples, not templates. Replace their fictional evidence paths and choose only the types the target project needs.
What ships with it
12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 266 B
- references/cli-contract.md 3.7 KB
- references/fixture-data-ml.json 2.3 KB
- references/fixture-embedded-iot.json 2.3 KB
- references/fixture-infrastructure.json 2.3 KB
- references/fixture-library-sdk.json 2.3 KB
- references/fixture-mobile-desktop.json 2.3 KB
- references/fixture-research-protocol.json 2.3 KB
- references/fixture-web-saas.json 2.2 KB
- references/paired-examples.md 6.9 KB
- references/project-suites.md 2.4 KB
- references/stage-types.md 4.1 KB
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.
- 12d ago First seen · 53 lines · 77 tokens per session scan A 8c020b2b69db
turritopsis-onboarding is a skill published in the GitHub repository anhe2021212-spec/Turritopsis (13 stars, last pushed 17d ago), licensed MIT. It adds 77 tokens to every session and 821 once invoked, about $0.0004 per session on Opus 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 2026-08-30.
Other skills, from other repositories
to-goal
Turn an approved spec, agent-ready ticket, tracker frontier, or partially implemented ticket into a verifiable execution goal without re-interviewing the user. Use after to-tickets or triage, before starting a fresh implementation session; use --all only for an explicitly requested cross-ticket goal.
handing-off-work
Hands off unfinished work with a closed-loop briefing of state, changed conditions, remaining scope, authority limits, and open evidence. Use when AI-agent, reviewer, verifier, releaser, or resumed-thread work transfers to a new owner. Do not use when the same owner continues uninterrupted with full context.
tracking-deficiencies
Keeps a standing register of known deficiencies so flaky tests, noisy alerts, unowned services, and recurring incidents get aged, owned, and fixed or formally risk-accepted instead of quietly normalized. Use when a known problem will outlive a single change. Do not use for a one-off lesson already closed inside a…
forward-plan
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handoff-inbox-drain
Use when draining a Brigade handoff review inbox - triage drafts with allowlist-bound Brigade handoff commands, grounded edits that cite on-disk content, archive-only retention, and reinforce-in-place when ingest already matched a known fact (#724). Never delete, remove, or prune.
pace-bridge
Use to bridge a confirmed Superpowers/native plan into PACEflow CHG/HOTFIX artifacts, create artifact-writer prompts, and mark the specific plan as synced.