Borrowing it
Nothing to install: this file belongs to agentculture/learn-cli. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/agentculture/learn-cli/main/.claude/skills/deviate/SKILL.mdgit clone --depth 1 https://github.com/agentculture/learn-cliWrote 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/agentculture/learn-cli/deviate)<a href="https://agentmods.dev/skills/agentculture/learn-cli/deviate"><img src="https://agentmods.dev/badge/skills/agentculture/learn-cli/deviate/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/agentculture/learn-cli/deviate"><img src="https://agentmods.dev/badge/skills/agentculture/learn-cli/deviate.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 | $0.00167 | $0.02398 |
| Opus 5.5 | $0.00067 | $0.00959 |
| Sonnet 5.5 | $0.00033 | $0.00480 |
| Haiku 4.5 | $0.00017 | $0.00240 |
Grade A, and why
deviate 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 2mo 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.
This is a copy
100% identical to deviate — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
deviate — record an approved mid-run departure from the confirmed plan
The skill is named deviate; it is the execution-time leg of the
devague method — the sixth leg, sitting between the two execution skills:
scope -> think -> spec-to-plan -> assign-to-workforce -> deviate -> summarize-delivery
Where /assign-to-workforce fans out a converged plan's waves and
/summarize-delivery closes the loop afterward, /deviate runs during
the fan-out, at the exact moment reality stops matching the plan the human
approved at gate 2 (the implementation split plan). It is not a new standing
gate — it is the human owner of gate 2 amending the approved split
mid-flight, scoped to the one deviation in front of them.
The plan the user confirmed is a contract. Task agents hit constraints,
discover a dependency was wrong, or find the acceptance criteria no longer
make sense once code is in front of them. Until this skill existed, that
reality either silently reshaped what got built (undocumented drift) or the
run stalled with no recorded path forward. /deviate is that path: the
departure is named, approved, and recorded before anyone keeps building
against it.
The method
- STOP the run. The moment a task agent (or the main agent) discovers the confirmed plan no longer matches what needs to happen, halt — do not keep implementing against the stale contract and do not let the fan-out continue past this task.
- Present what, why, and what it affects. Lay out, for the human:
- what is diverging — the specific change from the confirmed task(s);
- why — the constraint or discovery that forced it;
- what it affects — the plan item ref(s) involved (
--task), any other task ids or coverage targets it touches (--affects), and which acceptance criteria are no longer accurate.
- Get explicit human approval. This is the one non-negotiable step. A deviation is not real until a human says yes to this specific departure — not a standing blanket permission, not an inference from silence.
- Record it via
devague deviate. Once approved, record the deviation as a first-class ledger entry (never edit the plan itself — the plan stays the untouched historical contract; seedevague/delivery.py). An--origin llmrecord landsproposedand still needs the user's--confirm— recording is not the same as approval landing as final. - Adjust the affected task briefs. Update the working instructions the task agent(s) are building against so they reflect the approved departure, not the stale plan text.
- Resume. Only after the record exists (and, for an
llm-origin record, only after it is confirmed) does the fan-out continue.
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.
- 2mo ago First seen · 177 lines · 167 tokens per session scan A 083e1ab1b6cd
deviate is a skill published in the GitHub repository agentculture/learn-cli (1 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 167 tokens to every session and 2,398 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to deviate, differing in 0 lines, and is treated as a copy.
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