Agent skill

Conducty Review

by robertbarclayy in robertbarclayy/conducty

End-of-plan review sweep. An agent skill from robertbarclayy/conducty.

MITAuto-check passed

Install Conducty Review

skills CLI
$ npx skills add robertbarclayy/conducty --skill conducty-review -a claude-code

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

GitHub CLI
$ gh skill install robertbarclayy/conducty conducty-review --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/robertbarclayy/conducty.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/conducty-review .claude/skills/conducty-review && 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
conducty-review
GitHub stars
176
Token cost
~1.4k tokens
SKILL.md length
536 words
Files
1
Skills in repo
20
Repo updated
First seen
Licence
MIT

At a glance

End-of-plan review sweep. An agent skill from robertbarclayy/conducty.

  • Works in 8 steps: Load the Plan → Identify What Needs Review → Review Each Prompt → …
  • The user says review
  • SKILL.md covers Workflow and Principles
  • Calls git

What it does

Conducty Review is an agent skill from robertbarclayy/conducty. End-of-plan review sweep. Audits the plan's executed prompts, records verdicts with evidence, extracts failure patterns, computes velocity metrics, prepares carry-forward intelligence. Use when the user says "review", "audit", "review this plan", or at the end of a plan before [[conducty-improve]].

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: Stop context-switching. Start batch-planning. Conducty replaces the fragmented cycle of plan → prompt → wait → get distracted → review → fix → repeat with advanced batch planning. The licence is MIT.

When your agent uses it

  • The user says review
  • Review this plan
  • At the end of a plan before [[conducty-improve]]

Example prompts

  • “review”
  • “review this plan”
  • “/conducty-review”

Workflow steps

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

  1. Load the Plan
  2. Identify What Needs Review
  3. Review Each Prompt
  4. Record Verdicts
  5. Extract Failure Patterns
  6. Compute Velocity Metrics
  7. Prepare Carry-Forward
  8. Update Index + Hand Off to Improvement

What it can do on your machine

Read from SKILL.md and the folder at commit 64aefd5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    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

Conducty Review loads about 1.4k tokens when it runs. Until then it costs about 79 tokens; SKILL.md has 536 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~79
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

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 passed

The automated check found no risky patterns in SKILL.md.

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 robertbarclayy/conducty at commit 64aefd5, republished under its MIT licence (© robertbarclayy). 536 words, ~1,443 tokens.

Download SKILL.mdSave it as .claude/skills/conducty-review/SKILL.md (or your agent's skills folder).
name
conducty-review
description
End-of-plan review sweep. Audits the plan's executed prompts, records verdicts with evidence, extracts failure patterns, computes velocity metrics, prepares carry-forward intelligence. Use when the user says "review", "audit", "review this plan", or at the end of a plan before [[conducty-improve]].
aliases
conducty-review, review
tags
conducty/skill, conducty/review

Conducty Review — End-of-Plan Audit

Systematically review all executed prompts from the active plan, verify results with evidence, extract failure patterns for the learning system, and prepare intelligent carry-forward for the next plan.

Workflow

Step 1: Load the Plan

Read the active plan note from the vault (Plans/Plan YYYY-MM-DD HHmm [Topic].md — see [[conducty-obsidian]]). If the user is reviewing a different plan, ask which one and resolve the wikilink.

Parse the prompt queue to identify all prompts and their current status.

Step 2: Identify What Needs Review
  • Completed (from checkpoint): Already verified — confirm the checkpoint evidence is in the notes
  • Needs-fix with pending fixes: Check if the fix was applied
  • Unchecked: Not executed — skip, note as carry-forward
  • Already reviewed: Skip unless user requests re-review

Focus on prompts that completed since the last checkpoint or were fixed after checkpoint feedback.

Step 3: Review Each Prompt

For each prompt needing review:

  1. Check checkpoint evidence — if the prompt passed checkpoint, confirm the evidence is recorded
  2. If no checkpoint evidence: Run [[conducty-verify]] at the prompt's review level
  3. Check for unintended changes — git diff/git status (Bash) in the prompt's directory. Any files changed that weren't in the expected outcome?
  4. Confirm intent was met — does the actual change match the goal's design, not just the prompt's letter?
Step 4: Record Verdicts

For each prompt, record a verdict:

  • completed — changes verified, intent met, no issues
  • needs-fix — issues found, can be retried (increment Retries)
  • partial — some parts done, rest needs follow-up
  • failed — didn't produce useful results, needs rethinking
  • blocked — exceeded retries or needs manual intervention

Retry handling for needs-fix:

  1. Check Retries count
  2. If Retries < 3: invoke [[conducty-debug]] to determine leverage point, generate fix prompt
  3. If Retries >= 3: set to blocked with full history of attempts

Update each prompt's Status in the plan (Edit tool).

Show full SKILL.md (235 more words)Show less
Step 5: Extract Failure Patterns

For every non-completed prompt, analyze the failure and prepend an entry to [[Failure Patterns]] (the accumulating note in the vault — see [[conducty-obsidian]]):

markdown
### {YYYY-MM-DD HHmm} — P{N}: {description}
- **Plan**: [[Plan YYYY-MM-DD HHmm Topic]]
- **Leverage point**: plan / prompt / code
- **Symptom**: {what the failure looked like}
- **Root cause**: {what was actually wrong}
- **Prompt smells present**: {which smells were visible in retrospect}
- **Prevention**: {what would prevent this in future prompts}

Look for patterns across failures:

  • Same prompt smell appearing in multiple failures? → template problem
  • Same project failing repeatedly? → context is stale or incomplete
  • Same complexity level failing? → calibration is off
Step 6: Compute Velocity Metrics

Calculate and record in the plan note's ## End-of-Plan Summary:

markdown
## End-of-Plan Summary

- **Total prompts**: N
- **Completed**: N ({%})
- **First-attempt passes**: N ({%})
- **Needs fix**: N
- **Partial**: N
- **Failed**: N
- **Blocked**: N
- **Total retries**: N
- **Average retries per fix**: N
- **Appetite used**: {actual time} / {budgeted time}
- **Carry forward**: {prompt IDs with context}

Also prepend a row to [[Metrics]] (the accumulating note):

markdown
### {YYYY-MM-DD HHmm} — [[Plan YYYY-MM-DD HHmm Topic]]
- Prompts: {total} | Completed: {n} | Pass rate: {%} | Retries: {n}
- Appetite: {used}/{budget}
- Blocked: {n}
- Top failure pattern: {brief}

And prepend a per-prompt block to [[Prompt Log]] summarizing each prompt's outcome with verification evidence:

markdown
### {YYYY-MM-DD HHmm} — [[Plan YYYY-MM-DD HHmm Topic]]

- **P1** ({verify-only/spec-review/full-review}): pass — `command` exit 0, 12/12 tests
- **P2** (spec-review): needs-fix — see [[Failure Patterns]] entry
- ...
Step 7: Prepare Carry-Forward

For items carrying forward to the next plan, include carry-forward intelligence — not just "needs fix" but actionable context:

markdown
## Carry Forward

- **P{N}**: {description}
  - **Status**: needs-fix / partial / blocked
  - **What happened**: {brief history of attempts}
  - **Root cause**: {if identified}
  - **Recommended approach**: {what to try differently}
  - **Leverage point**: {plan / prompt / code}

This is what [[conducty-plan]] reads in Step 1 of the next plan. Make it useful.

Step 8: Update Index + Hand Off to Improvement

Confirm the plan's wikilink is in [[Plans Index]]. Then:

After the review is complete, invoke [[conducty-improve]] for the per-plan learning loop. The review provides the data; the improvement kata extracts the lessons.

Principles

  • Evidence-based verdicts — every verdict references verification output, not impressions
  • Failure patterns are the most valuable output — they prevent future failures
  • Carry-forward intelligence saves the next plan — "needs fix" with context is 10x more useful than "needs fix" alone
  • Metrics track system health — pass rate trend tells you if the process is improving
  • Review feeds improvement — this step produces data, [[conducty-improve]] produces change

© robertbarclayy, 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/conducty-review of robertbarclayy/conducty.

Open the folder on GitHubat commit 64aefd5

Compare with similar skills

Conducty Review 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.

Conducty Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Conducty Review this skillrobertbarclayy/conducty176—~1.4kAutomated safety check: PassMIT
Executealirezarezvani/claude-skills28k—~831Automated safety check: PassMIT
Debugging Executionsn8n-io/n8n207k—~2.6kAutomated safety check: PassCustom licence
Production Auditaffaan-m/ECC277k1 repos~1.9kAutomated safety check: PassMIT
Aims Auditalirezarezvani/claude-skills28k—~1.3kAutomated safety check: PassMIT
Geo Auditsickn33/agentic-awesome-skills47k1 repos~3.4kAutomated safety check: NotesMIT

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  • Conducty Debug

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  • Conducty Improve

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Questions about Conducty Review

What does Conducty Review do?

End-of-plan review sweep. An agent skill from robertbarclayy/conducty. Conducty Review is an agent skill from robertbarclayy/conducty. End-of-plan review sweep.

When should I use Conducty Review?

Conducty Review fits situations like: the user says review; review this plan; at the end of a plan before [[conducty-improve]].

How do I install Conducty Review in Claude Code?

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

How do I install Conducty Review in Codex?

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

Can I use Conducty Review 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 robertbarclayy/conducty --skill conducty-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/conducty-review, .gemini/skills/conducty-review, .github/skills/conducty-review and .opencode/skills/conducty-review in your project.

What does Conducty Review need to run?

Going by SKILL.md and its folder, Conducty Review needs the command-line tools its instructions call (git).

Does Conducty Review 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 Conducty Review safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Conducty Review use?

Conducty Review 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 Conducty Review use?

About 1.4k tokens (SKILL.md is roughly 5.8k 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 Conducty Review?

Skills that share tags, products or a category with Conducty Review: Execute (alirezarezvani/claude-skills, 28k stars), Debugging Executions (n8n-io/n8n, 207k stars), Production Audit (affaan-m/ECC, 277k stars) and Aims Audit (alirezarezvani/claude-skills, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Conducty Review?

robertbarclayy (a GitHub user) maintains it in robertbarclayy/conducty, which has 176 GitHub stars. The repository holds 20 skills in this directory. The repository was last updated on June 19, 2026.

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