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 appautomaton/automaton --skill auto-eng-reviewgit clone --depth 1 https://github.com/appautomaton/automatonWrote 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/appautomaton/automaton/auto-eng-review)<a href="https://agentmods.dev/skills/appautomaton/automaton/auto-eng-review"><img src="https://agentmods.dev/badge/skills/appautomaton/automaton/auto-eng-review/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/appautomaton/automaton/auto-eng-review"><img src="https://agentmods.dev/badge/skills/appautomaton/automaton/auto-eng-review.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 | $0.00022 | $0.01036 |
| Opus 5 | $0.00011 | $0.00518 |
| Sonnet 5 | $0.00004 | $0.00207 |
| Haiku 4.5 | $0.00002 | $0.00104 |
Grade A, and why
auto-eng-review 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 10d 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
auto-eng-review
Optional engineering-safety review. Validates that a plan is safe to execute before implementation begins.
First action: run node .agent/.automaton/scripts/get-context.mjs from the project root.
Preamble
Execution safety review. Architecture, data flow, edge cases, test strategy, not product vision. It does not change the plan's content or reopen product scope; its only write is appending its own ## Review: Engineering section. Identifies risks that could cause failure, stalling, or rework.
A good review names the riskiest slice, the most likely failure mode, and whether the test strategy catches it. A bad review lists generic concerns.
Loading discipline: one PLAN.md read, optional DESIGN.md when canonical_design exists, one risk matrix, one verdict. Read source files when assessing technical risk: slice boundaries, dependency assumptions, and blast radius claims are only verifiable against the actual code.
Quality Gate
Before appending the engineering review:
- Ground concerns in slices, file areas, commands, or missing artifacts.
- Separate blockers from follow-up cleanup.
- Avoid reopening product scope unless the plan is unbuildable.
- Read
references/quality.mdwhen findings are generic or unactionable.
Do
Do NOT proceed unless:
canonical_planis set andPLAN.mdis readable.
If the plan is missing or unreadable, set verdict to needs_correction and stop.
Load State
Read the canonical PLAN.md. Read DESIGN.md only when canonical_design is set and resolves to a file. An unset pointer means the plan intentionally has no design artifact; continue without it. A set pointer with a missing file is stale: report it and continue (DESIGN.md is optional here).
Restate the Plan
In engineering terms: what is being built, what systems does it touch, and what is the critical path?
Evaluate Risks
Use this matrix as an internal checklist. Apply standards from references/prime-directives.md while evaluating.
What ships with it
6 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.
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.
- 10d ago First seen · 97 lines · 22 tokens per session scan A 366c3bb95449
auto-eng-review is a skill published in the GitHub repository appautomaton/automaton (21 stars, last pushed 23d ago), licensed MIT. It adds 22 tokens to every session and 1,036 once invoked, about $0.0001 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
wiki-ingest
Ingest a source into the project wiki as OKF v0.2 markdown. Point at a file, PR, or doc and the wiki-curator extracts knowledge, writes YAML frontmatter, and updates relevant concept pages.
wiki-lint
Health-check the project wiki for OKF v0.2 conformance — missing frontmatter, missing type:, malformed index.md/log.md, stale pages past staleafter, broken cross-references, and coverage gaps.
agent-carnet
Use this skill when the user asks to save, recall, find, or organize notes. Triggers on: 'remember this', 'save this', 'note this', 'what did we discuss about...', 'check the notebook', 'find in carnet'. Also use proactively when discovering findings worth preserving across sessions.
deploy-docker-compose
Run the Omnigent server as a Docker compose stack (server + Postgres) on any Docker host — your laptop, a VPS, EC2 by hand, or as the base layer of any container-platform deploy. Invoke when the user wants to build the image, bring up the compose stack, debug the stack on a host they already have, or extend the stack…
security-audit
Audit a codebase or directory for security issues (hardcoded secrets, injection, unsafe deserialization, weak crypto, authz gaps) and produce a structured findings report. Use when the user asks for a security review, an audit, or to check code for vulnerabilities. Report only — never fix.
taiyi-ui-design
A design-planning guide for describing how an application's user interface should look and behave. It produces a UI-DESIGN.md document covering layouts, components, interactions, accessibility, and error states.