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 raine/consult-llm --skill implementgit clone --depth 1 https://github.com/raine/consult-llmWrote 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/raine/consult-llm/implement)<a href="https://agentmods.dev/skills/raine/consult-llm/implement"><img src="https://agentmods.dev/badge/skills/raine/consult-llm/implement/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/raine/consult-llm/implement"><img src="https://agentmods.dev/badge/skills/raine/consult-llm/implement.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 46 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00071 | $0.02301 |
| Opus 5.5 | $0.00028 | $0.00920 |
| Sonnet 5.5 | $0.00014 | $0.00460 |
| Haiku 4.5 | $0.00007 | $0.00230 |
Grade A, and why
implement 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.
How it starts
The opening of the file, as written. The whole thing — 289 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implement workflow
Implement one bounded unit in the current worktree. Prefer the smallest complete change that satisfies the requested behavior. The current agent researches and implements the unit directly, so do not write the implementation twice as a code-bearing plan.
Presets increase required evidence, not architecture, abstractions, tests, or documentation.
Arguments
Arguments are $ARGUMENTS.
Parse these flags before starting:
--preset light|standard|design|strict: defaultstandard--parent-plan <path>: authoritative scope or phase brief--reviewer <selector>: consult-llm reviewer selector, repeatable--reviewers <selector,selector>: comma-separated reviewer selectors--validation <command>: expected validation command
Everything else is the implementation request.
Presets:
light: an established local pattern, focused validation, no external reviewstandard: the default, acceptance evidence and runtime exercise where applicable, no routine external reviewdesign: a meaningful API, ownership, or architecture choice, with one source-grounded technical-shape review before editsstrict: authentication, secrets, untrusted input, protocols, migrations, persistence, destructive behavior, concurrency, or FFI, with boundary-focused evidence and one final diff review
Treat a component with a strict boundary as strict even when the selected preset is lighter. Strictness adds relevant proof. It does not justify speculative hardening.
Do not ask the user during the workflow unless continuing safely requires a material product choice, public or irreversible contract, dependency, durable-state change, trust-model change, unsafe overwrite, or major scope expansion.
Working record
Keep at most one evolving implementation brief under history/ with today's
date prefix. A brief is required only when:
- the preset is
designorstrict - the caller explicitly requests one
- discoveries are complex enough that a durable execution record prevents mistakes
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 Changed · -90 lines · +19 tokens per session aaaff0ad867e
- 1mo ago First seen · 379 lines · 52 tokens per session scan A ef6e711ce149
implement is a skill published in the GitHub repository raine/consult-llm (142 stars, last pushed 14d ago), licensed MIT. It adds 71 tokens to every session and 2,301 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 2026-08-30.
Other skills, from other repositories
autoreview
Structured code review through the shared OpenClaw agent-skills installation.
omh-code-review
This is an OMH code-review workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).
revdiff-plan
Review the last Codex assistant message (plan, analysis, or proposal) with inline annotations in a TUI overlay. Extracts the most recent response from Codex rollout files and opens it in revdiff for review and annotation. Activates on "revdiff-plan", "review plan with revdiff", "annotate plan", "review last response"…
re0-merge
Review and land an external contribution the way this suite does: gate it against the thesis, land it with the author's credit intact, complete a new skill rather than merging it raw, then approve, credit, and explain before closing. Use when reviewing a pull request, as any collaborator or maintainer, not only the…
explore-unknowns
Guide the user through a quadrant walk that maps the unknowns of a task — open by listing the known knowns, then work through known unknowns, unknown knowns, and unknown unknowns one stage at a time, ending with a complete four-quadrant map in the user's hands. Use when a request is ambiguous or underspecified, the…
asplos-writing-style
Use when drafting or revising ASPLOS prose — engineering the first two pages that rapid review actually reads, stating the cross-layer insight as one quotable sentence, structuring per-layer mechanism sections, writing bounded claims, and fitting everything into 11 self-contained pages that include figures and…