Agent skill

Bmad Review

by delorenj in delorenj/mcp-server-trello

Multi-lens review over any diff, doc, spec, or artifact — whichever installed lenses fit the content, run singly or together.

MITAuto-check passedWriting & Content

Install Bmad Review

skills CLI
$ npx skills add delorenj/mcp-server-trello --skill bmad-review -a claude-code

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

GitHub CLI
$ gh skill install delorenj/mcp-server-trello bmad-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/delorenj/mcp-server-trello.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agent/skills/bmad-review .claude/skills/bmad-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
bmad-review
GitHub stars
445
Token cost
~1.9k tokens
SKILL.md length
984 words
Files
11 (incl. scripts, references)
Skills in repo
64
Repo updated
First seen
Licence
MIT

At a glance

Multi-lens review over any diff, doc, spec, or artifact — whichever installed lenses fit the content, run singly or together.

  • Works in 7 steps: Resolve customization: uv run… → Load the content. If it is empty or… → Select lenses from {workflow.lenses}. A… → …
  • The user says review this
  • SKILL.md covers Inputs, Conventions, Execution and Output
  • Runs Python scripts from its folder; calls uv

What it does

Bmad Review is an agent skill from delorenj/mcp-server-trello. Multi-lens review over any diff, doc, spec, or artifact — whichever installed lenses fit the content, run singly or together. Shipped lenses include adversarial, edge-case, verification-gap, structure, and prose. Use when the user says "review this", "critical review", "editorial review", "hunt edge cases", "review the structure", or "review the prose".

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 13 other files, including scripts and reference files (for example `references/editorial-common.md`, `references/lens-adversarial.md` and `references/lens-edge-case-hunter.md`).

It sits in Writing & Content, covering Copy editing and proofreading. The repository describes itself as: A Model Context Protocol (MCP) server that provides tools for interacting with Trello boards. The licence is MIT.

When your agent uses it

  • The user says review this
  • Critical review
  • Editorial review
  • Hunt edge cases

Example prompts

  • “review this”
  • “critical review”
  • “editorial review”
  • “/bmad-review”

Requirements

  • Python 3

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Resolve customization: uv run {project-root}/_bmad/scripts/resolve_customization.py --skill {skill-root} --key workflow. On failure, read…
  2. Load the content. If it is empty or cannot be decoded as text: when the caller expects the raw findings JSON array (e.g. the legacy…
  3. Select lenses from {workflow.lenses}. A lens with an empty instruction is disabled. If the user or caller named lenses, run exactly those…
  4. Announce the plan in one line before running anything: the content class, the lenses about to run, and — when any lens has after set…
  5. Run the independent lenses — every selected lens without after. Each sees the content and also_consider, never another lens's findings…
  6. Run the dependent lenses — every selected lens with after, once the lens it names has completed, passing that lens's findings in. A lens…
  7. Assemble and present per Output below. Keep every lens's findings — overlap between lenses is signal, not duplication; note it in the…

What it can do on your machine

Read from SKILL.md and the folder at commit 737292f. 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

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • uv

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

  • Network

    No URLs in SKILL.md. Its commands use uv, 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

Bmad Review loads about 1.9k tokens when it runs, and up to ~7.9k if it reads all its reference files. Until then it costs about 92 tokens; SKILL.md has 984 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~92
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~7.9k

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 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); the scripts in this folder are not scanned.

SKILL.md

The full file from delorenj/mcp-server-trello at commit 737292f, republished under its MIT licence (© delorenj). 984 words, ~1,851 tokens.

Download SKILL.mdSave it as .claude/skills/bmad-review/SKILL.md (or your agent's skills folder). This skill also uses 10 other files; get the full folder from GitHub.
name
bmad-review
description
Multi-lens review over any diff, doc, spec, or artifact — whichever installed lenses fit the content, run singly or together. Shipped lenses include adversarial, edge-case, verification-gap, structure, and prose. Use when the user says "review this", "critical review", "editorial review", "hunt edge cases", "review the structure", or "review the prose".

BMad Review

Review content through lenses — each a distinct method and stance — and report findings in one canonical shape. Report what is real — never pad to look thorough. Each lens sets its own stance toward the content and toward zero findings: for most an empty result is valid; the adversarial lens treats it as suspicious; the editorial lenses hold content sacrosanct and critique only how it is organized and expressed.

The lens set is whatever {workflow.lenses} resolves to, not a fixed list — overrides add lenses and replace shipped ones. Never claim a capability from this file; read the resolved lenses and work from those.

Inputs

  • content — what to review: a diff, branch, uncommitted changes, file, spec, story, or any document. Args: [path].
  • lenses (optional) — one or more lens codes or names, however the caller expresses them: a spoken request, or a directive of the form skill:bmad-review lenses=<code>[,<code>...] (the form bmm's doc_standards uses). Default: every applicable lens (a full review).
  • also_consider (optional) — areas to keep in mind alongside each lens's normal analysis.
  • pre-resolved customization (optional) — [workflow] field values supplied by a forwarding caller. See Execution step 1.

Conventions

  • Bare paths (e.g. references/lens-edge-case-hunter.md) resolve from {skill-root} — this skill's installed directory, where customize.toml lives. {project-root} resolves to the project working directory.
  • {workflow.<name>} resolves to fields in customize.toml's [workflow] table (overrides win per BMad merge rules).
  • In style_guide, review_guidance, and persistent_facts, a value prefixed file: is a path or glob — load that file's contents. If a file: value cannot be read, name the failed file in the output header and continue: the shipped baseline for style_guide, the remaining entries otherwise.

Execution

  1. Resolve customization: uv run {project-root}/_bmad/scripts/resolve_customization.py --skill {skill-root} --key workflow. On failure, read {skill-root}/customize.toml directly and use defaults. Forwarded activation: if a caller invoked you with pre-resolved customization fields (e.g. the bmad-editorial-review shim), honor them verbatim for those named fields — they already carry the user's overrides — and resolve only the remaining fields from your own customize.toml. Then execute each {workflow.activation_steps_prepend} entry in order, hold {workflow.persistent_facts} as standing context for the session, and treat {workflow.review_guidance} entries as standing review directives for every lens.
  2. Load the content. If it is empty or cannot be decoded as text: when the caller expects the raw findings JSON array (e.g. the legacy edge-case forwarder), return [{"location":"N/A","trigger_condition":"Input empty or undecodable","guard_snippet":"Provide valid content to review","potential_consequence":"Review skipped — no analysis performed"}] (no lens field) and stop; otherwise say what's wrong and ask for reviewable content. Classify the content — diff, source file, function, or document — and whether it is code or docs; scope rules and lens applicability both depend on it. A document that defines behavior (spec, requirements, plan, story) is docs that a behavioral lens may still apply to; judge by when.
  3. Select lenses from {workflow.lenses}. A lens with an empty instruction is disabled. If the user or caller named lenses, run exactly those only — applies_to and when do not filter an explicit request. Otherwise run every enabled lens whose applies_to covers the content class (any always covers) and whose when applies.
  4. Announce the plan in one line before running anything: the content class, the lenses about to run, and — when any lens has after set — that it runs on top of the named lens's findings. Skip the announcement entirely when the caller pinned an exact output contract (the legacy forwarders that demand raw JSON or one exact line) — their contract covers everything you emit, not just the findings block. Then execute each {workflow.activation_steps_append} entry in order.
  5. Run the independent lenses — every selected lens without after. Each sees the content and also_consider, never another lens's findings. Follow each lens's instruction; the shipped lenses load their reference file just-in-time, so load only what runs. When subagents are available, spawn one per lens in parallel: give it the lens instruction with {skill-root} and paths resolved absolute, the content or where to read it, any also_consider areas, the standing review directives, and the constraint "Return ONLY your findings — no other output." Otherwise run the lenses sequentially yourself, completing one before starting the next.
  6. Run the dependent lenses — every selected lens with after, once the lens it names has completed, passing that lens's findings in. A lens whose after target was not selected or produced nothing still runs, with no prior findings. Dependent lenses that name different targets are independent of each other and may run in parallel.
  7. Assemble and present per Output below. Keep every lens's findings — overlap between lenses is signal, not duplication; note it in the markdown report rather than deduping. Execute {workflow.on_complete} if set.
Show full SKILL.md (226 more words)Show less

Output

One JSON array holding every finding from every lens. Each finding carries:

  • lens — the code of the lens that produced it
  • location — where in the content (file:line-range for code, section for documents)
  • trigger_condition — the problem, or the condition that exposes it, in one line
  • guard_snippet — the concrete fix, guard, or missing check
  • potential_consequence — what goes wrong if it ships as-is

Each lens file refines these semantics for its findings and may add lens-specific fields (e.g. kind/confidence on deletion findings, gap_shape/consumer/evidence on verification-gap findings). A lens file may instead declare its own findings shape and rendering — the editorial lenses render a findings table — and that shape wins for that lens's findings. [] is valid when nothing is found. No severity, priority, or ranking anywhere.

Present per {workflow.output_format} — "json" (the raw array in a fenced json block), "markdown", or "both" — unless the caller requested a specific shape; a legacy forwarder's output contract always wins, and governs everything you emit rather than the findings block alone. The markdown report groups findings by lens, each rendered in its declared shape: a short block per finding rendering the fields plus any extras worth surfacing, one line for a lens that found nothing, and a plain clean statement when the whole review is clean. Shape the report per {workflow.output_preferences}.

When {workflow.report_path} is set, write the report there; otherwise present it in chat.

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

Files

SKILL.md and 10 other files (scripts, references) in .agent/skills/bmad-review of delorenj/mcp-server-trello.

  • SKILL.md
  • customize.toml
  • references/editorial-common.md
  • references/lens-adversarial.md
  • references/lens-edge-case-hunter.md
  • references/lens-prose.md
  • references/lens-structure.md
  • references/lens-verification-gap.md
  • references/structure-models.md
  • scripts/tests/test_word_metrics.py
  • scripts/word_metrics.py

Open the folder on GitHubat commit 737292f

Compare with similar skills

Bmad 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.

Bmad Review compared with similar skills
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Bmad Review this skilldelorenj/mcp-server-trello445—~1.9kAutomated safety check: PassMIT
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Story Multi-Perspective Reviewzenstory-ai/oh-story-claudecode7.4k3 repos~3kAutomated safety check: PassMIT
Chinese Text Humanizerop7418/Humanizer-zh19k—~2kAutomated safety check: PassMIT
Baoyu TranslateJimLiu/baoyu-skills27k1 repos~3.9kAutomated safety check: PassMIT
Natural Japanese Business Writingcoji/natural-japanese1.9k—~2.1kAutomated safety check: PassMIT

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Questions about Bmad Review

What does Bmad Review do?

Multi-lens review over any diff, doc, spec, or artifact — whichever installed lenses fit the content, run singly or together. Bmad Review is an agent skill from delorenj/mcp-server-trello. Multi-lens review over any diff, doc, spec, or artifact — whichever installed lenses fit the content, run singly or together.

When should I use Bmad Review?

Bmad Review fits situations like: the user says review this; critical review; editorial review; hunt edge cases.

How do I install Bmad Review in Claude Code?

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

How do I install Bmad Review in Codex?

Run `npx skills add delorenj/mcp-server-trello --skill bmad-review -a codex`. Or copy the skill folder (.agent/skills/bmad-review in delorenj/mcp-server-trello) into .agents/skills/bmad-review in your project. Codex loads it when a task matches its description.

Can I use Bmad 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 delorenj/mcp-server-trello --skill bmad-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/bmad-review, .gemini/skills/bmad-review, .github/skills/bmad-review and .opencode/skills/bmad-review in your project.

What does Bmad Review need to run?

Going by SKILL.md and its folder, Bmad Review needs Python for the scripts in its folder and the command-line tools its instructions call (uv). Our summary lists: Python 3.

Does Bmad Review access the network?

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

Is Bmad 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Bmad Review use?

Bmad 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 Bmad Review use?

About 1.9k tokens (SKILL.md is roughly 7.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 6.1k tokens, read only when the agent opens those files.

What are the alternatives to Bmad Review?

Skills that share tags, products or a category with Bmad Review: User-Facing Text Cleanup (guillaumemeyer/watermarks-remover, 24k stars), Story Multi-Perspective Review (zenstory-ai/oh-story-claudecode, 7.4k stars), Chinese Text Humanizer (op7418/Humanizer-zh, 19k stars) and Baoyu Translate (JimLiu/baoyu-skills, 27k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Bmad Review?

delorenj (a GitHub user) maintains it in delorenj/mcp-server-trello, which has 445 GitHub stars. The repository holds 64 skills in this directory. The repository was last updated on September 23, 2026.

Source: delorenj/mcp-server-trello on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.