Agent skill

Implement

by raine in raine/consult-llm

Explicit workflow for one bounded implementation using source-grounded discovery, a walking slice, evidence-gated review, validation, and commit.

MITAuto-check: notesKnowledge Management

Install Implement

skills CLI
$ npx skills add raine/consult-llm --skill implement -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install raine/consult-llm implement --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/raine/consult-llm.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/implement .claude/skills/implement && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
implement
GitHub stars
140
Token cost
~2.9k tokens
SKILL.md length
1,322 words
Files
1
Skills in repo
12
Repo updated
First seen
Licence
MIT

At a glance

Explicit workflow for one bounded implementation using source-grounded discovery, a walking slice, evidence-gated review, validation, and commit.

  • Works in 5 steps: Establish facts → Review the technical shape when required → Implement a walking slice → …
  • Invokes /implement
  • SKILL.md covers Arguments, Working record, 1. Establish facts and 2. Review the technical shape…, plus 3 more sections
  • Calls git

What it does

Implement is an agent skill from raine/consult-llm. Explicit workflow for one bounded implementation using source-grounded discovery, a walking slice, evidence-gated review, validation, and commit. Use only when the user invokes /implement or another skill explicitly delegates to it. Do not trigger for ordinary coding requests, follow-up edits, fixes with an established design, or requests to amend an existing commit.

Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Knowledge Management, covering Source-grounded notebooks. The repository describes itself as: Get a second opinion from another AI model. The licence is MIT.

When your agent uses it

  • Invokes /implement
  • Another skill explicitly delegates to it
  • Ordinary coding requests
  • Follow-up edits

Example prompts

  • “/implement”

Requirements

  • Pre-approved tools (allowed-tools): Bash, Glob, Grep, Read, Edit, Write

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Establish facts
  2. Review the technical shape when required
  3. Implement a walking slice
  4. Exercise, simplify, and validate
  5. Commit and report

What it can do on your machine

Read from SKILL.md and the folder at commit 69e3ecb. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Bash
    • Glob
    • Grep
    • Read
    • Edit
    • Write

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Implement loads about 2.9k tokens when it runs. Until then it costs about 95 tokens; SKILL.md has 1,322 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~95
When it runs · the whole SKILL.md, loaded when a task matches
~2.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Bash, Glob, Grep, Read, Edit, Write

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from raine/consult-llm at commit 69e3ecb, republished under its MIT licence (© raine). 1,322 words, ~2,854 tokens.

Download SKILL.mdSave it as .claude/skills/implement/SKILL.md (or your agent's skills folder).
name
implement
description
Explicit workflow for one bounded implementation using source-grounded discovery, a walking slice, evidence-gated review, validation, and commit. Use only when the user invokes `/implement` or another skill explicitly delegates to it. Do not trigger for ordinary coding requests, follow-up edits, fixes with an established design, or requests to amend an existing commit.
allowed-tools
Bash, Glob, Grep, Read, Edit, Write

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: default standard
  • --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 review
  • standard: the default, acceptance evidence and runtime exercise where applicable, no routine external review
  • design: a meaningful API, ownership, or architecture choice, with one source-grounded technical-shape review before edits
  • strict: 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 design or strict
  • the caller explicitly requests one
  • discoveries are complex enough that a durable execution record prevents mistakes

A sufficient parent plan replaces the brief. Add a local note only for material facts or deviations absent from the parent plan.

Use this compact shape when a brief is needed:

markdown
# Implement: <topic>

**Goal:** <one observable outcome>
**Preset:** <preset>
**Parent plan:** <path or n/a>
**Validation:** <commands>

## Scope

- In:
- Out:

## Source facts

- `<path>:<symbol>`: <ownership, contract, or convention>

## Technical shape

- Existing mechanisms to reuse:
- Smallest complete slice:
- Acceptance evidence:
- Real trust or compatibility boundaries:
- Stop conditions:

## Accepted review findings

- <only independently reproduced findings>

## Result

- Acceptance evidence:
- Validation:
- Commit:
- Blockers:

Do not pre-write source or test code in the brief. Do not create separate plans, proposal captures, feedback ledgers, or review transcripts. Update the brief only when scope, technical ownership, accepted evidence, or the result changes. Briefs are workflow records. Do not stage or commit them.

A result sentinel is a separate artifact only when a parent plan or caller requires one.

1. Establish facts

  1. Read active repository instructions and relevant architecture documentation.
  2. Record git rev-parse HEAD and inspect git status --short.
  3. Stop before overwriting or unsafely entangling unrelated user changes.
  4. Read a supplied parent plan and treat its scope and acceptance criteria as authoritative.
  5. Find the nearest existing implementation, callers, tests, configuration, and runtime path. Prefer repository mechanisms over new ones.
  6. Define the observable outcome, explicit non-goals, smallest complete slice, actual trust or compatibility boundaries, and acceptance evidence.
  7. Select the narrowest useful focused checks plus every repository-required check. Use --validation unless it is plainly wrong.

Do not invent future consumers, extension points, defensive layers, or tests for unchanged framework behavior.

2. Review the technical shape when required

Skip this section unless the preset is design. A run receives at most one external review. Do not run a second review to approve corrections.

Before calling consult-llm, load the consult-llm skill and follow its invocation contract. Attach the brief or parent plan and focused source files. Use --task review, supplied reviewer selectors when present, the quoted heredoc terminator __CONSULT_LLM_END__, and Bash timeout 600000.

Ask whether the technical shape demonstrably conflicts with source-established ownership, behavior, contracts, or trust boundaries. Do not ask for a replacement plan or general hardening advice.

Every reported finding must include:

  • Claim: the specific incorrect behavior, contradiction, or execution blocker
  • Trigger: the concrete input, state, caller, or plan step that exposes it
  • Expected: the acceptance criterion, existing contract, repository convention, or real boundary requirement
  • Actual: the behavior the proposed shape would produce
  • Evidence: exact files and symbols plus a manual procedure, command, or complete reachable source trace
  • Smallest correction: the minimum change that fixes the issue
  • Verification: the check that proves the correction

Tell the reviewer to return no findings when no issue meets this standard. General hardening, hypothetical edge cases, style preferences, alternative valid designs, and speculative callers are not findings.

Independently confirm each finding before accepting it. For a pre-implementation finding, compare the named plan step with the complete current source path and identify the exact contract or acceptance criterion that would fail. Reviewer assertions alone are not evidence.

Ignore findings that cannot be reproduced, have no reachable trigger, protect no accepted behavior or real boundary, duplicate lower-layer guarantees, or ask for more hardening than the demonstrated issue requires. Record only accepted findings and their smallest corrections in the brief. Do not preserve rejected feedback in a ledger.

Show full SKILL.md (569 more words)Show less

3. Implement a walking slice

Implement serially in the current worktree:

  1. Build the thinnest complete path through existing owners.
  2. Reuse repository conventions before adding state, types, helpers, or error layers.
  3. Add an early test only when it captures a demonstrated regression, pure contract, parser, protocol invariant, or trust-boundary invariant needed to make the slice safe.
  4. Compile or run the changed path as soon as it works.
  5. Add remaining tests only when they prove accepted behavior, platform behavior, compatibility, a demonstrated regression, or a real trust boundary.
  6. Keep provisional APIs local and easy to reshape until a real second consumer proves a broader boundary.

Continue with best judgment when a correction preserves accepted behavior, reduces complexity, follows an existing convention, and stays within scope. Stop only when a stop condition from the opening section fires.

Revisit the technical shape when implementation introduces a generic mechanism, pass-through layer, one-consumer abstraction, unexplained convention deviation, or material scope growth. Prefer deletion or a smaller local form.

4. Exercise, simplify, and validate

For every acceptance criterion, obtain concrete evidence from a focused test, manual reproduction, real process or application exercise, or source proof for a static contract.

For standard and above, exercise the changed runtime path and one representative failure or constrained state when applicable. For strict components, verify only the relevant input, authorization, persistence, compatibility, error, cancellation, allocation, and destructive-state boundaries.

Audit the actual diff for:

  • unexplained scope growth or ownership changes
  • accidental overwrite of user changes
  • duplicated logic or tests
  • pass-through layers and single-consumer abstractions
  • tests of unchanged framework behavior
  • protections that must remain at real trust or compatibility boundaries

Run all focused validation and repository-required checks.

Conditional final diff review

Run one final diff review only for strict, or when the implementation materially diverges from the technical shape or changes a public or generic framework contract. If a design run already used its review, verify the diff directly instead. Never create a review cycle.

Load the consult-llm skill and use the same invocation requirements from section 2. Attach the diff, acceptance criteria, and focused source context. Ask for deletion-first review and concrete correctness findings. Require every finding to use the Claim, Trigger, Expected, Actual, Evidence, Smallest correction, and Verification fields above.

The reviewer must not report hypothetical failures, speculative compatibility, defense-in-depth without a real boundary, new extensibility, unchanged framework behavior, style preferences, or alternative valid designs. A minimality finding must identify exact code that serves no accepted behavior or real boundary.

Before changing code, independently reproduce each finding through the real entry point, a safe command, or a complete source trace from a real boundary to the failure. For unsafe or destructive triggers, source proof must demonstrate the reachable path and violated invariant without executing harm. For a minimality finding, confirm the existing owner or single consumer, apply the smallest safe deletion, and rerun the relevant evidence.

Apply only the smallest correction that resolves a reproduced issue. Ignore unreproduced suggestions. Do not request follow-up review. If a reproduced fix requires redesign or scope expansion, stop and report the blocker.

5. Commit and report

Commit when acceptance evidence and required validation pass, no blocker remains, and repository instructions permit committing. Never commit workflow records.

When a result sentinel is required, follow the caller's exact path and format. Write it after committing so its commit fields are final. If the caller supplies no format, use:

markdown
# Implementation Result: <topic>

status: success | blocked | failed
head_commit: <sha or pending>
commit: <sha or pending>
validation: <commands>
validation_status: passed | failed | skipped

## Summary

- <what changed>

## Acceptance

- <criterion>: met | not met | unknown, with evidence

## Blockers

- <blocker or none>

Report concisely:

markdown
## Result

- Outcome: <observable result>
- Main implementation: <owners and mechanisms reused>
- Acceptance evidence: <tests or runtime proof>
- Review: <none | accepted reproduced findings | blocker>
- Validation: <commands and results>
- Commit: <sha or reason absent>
- Remaining risks: <none or bounded demonstrated risks>
- Sentinel: <path or n/a>

© raine, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/implement of raine/consult-llm.

Open the folder on GitHubat commit 69e3ecb

Compare with similar skills

Implement next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Implement compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Implement this skillraine/consult-llm140—~2.9kAutomated safety check: NotesMIT
Zlibrary To Notebooklmzstmfhy/zlibrary-to-notebooklm1.7k1 repos~968Automated safety check: PassMIT
Multi-Source to NotebookLM Processorjoeseesun/qiaomu-anything-to-notebooklm6.2k—~3.6kAutomated safety check: PassMIT
Learn From Materialsdmoshehun-prog/learn-from-materials937—~7.9kAutomated safety check: PassMIT
NotebookLM Research Workflowclaude-world/notebooklm-skill467—~1.8kAutomated safety check: PassMIT
Nlmtmc/nlm390—~2.2kAutomated safety check: NotesMIT

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Questions about Implement

What does Implement do?

Explicit workflow for one bounded implementation using source-grounded discovery, a walking slice, evidence-gated review, validation, and commit. Implement is an agent skill from raine/consult-llm. Explicit workflow for one bounded implementation using source-grounded discovery, a walking slice, evidence-gated review, validation, and commit.

When should I use Implement?

Implement fits situations like: invokes /implement; another skill explicitly delegates to it; ordinary coding requests; follow-up edits.

How do I install Implement in Claude Code?

Run `npx skills add raine/consult-llm --skill implement -a claude-code`. Or copy the skill folder (skills/implement in raine/consult-llm) into .claude/skills/implement in your project. Claude Code loads it when a task matches its description.

How do I install Implement in Codex?

Run `npx skills add raine/consult-llm --skill implement -a codex`. Or copy the skill folder (skills/implement in raine/consult-llm) into .agents/skills/implement in your project. Codex loads it when a task matches its description.

Can I use Implement in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add raine/consult-llm --skill implement -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/implement, .gemini/skills/implement, .github/skills/implement and .opencode/skills/implement in your project.

What does Implement need to run?

Going by SKILL.md and its folder, Implement needs the command-line tools its instructions call (git). Its frontmatter pre-approves these tools: Bash, Glob, Grep, Read, Edit, Write.

Does Implement access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Implement safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Implement use?

Implement is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Implement use?

About 2.9k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Implement?

Skills that share tags, products or a category with Implement: Zlibrary To Notebooklm (zstmfhy/zlibrary-to-notebooklm, 1.7k stars), Multi-Source to NotebookLM Processor (joeseesun/qiaomu-anything-to-notebooklm, 6.2k stars), Learn From Materials (dmoshehun-prog/learn-from-materials, 937 stars) and NotebookLM Research Workflow (claude-world/notebooklm-skill, 467 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Implement?

raine (a GitHub user) maintains it in raine/consult-llm, which has 140 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on October 7, 2026.

Source: raine/consult-llm on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.