Agent skill

Planning

by mblode in mblode/agent-skills

Creates and reviews executable implementation plans grounded in repository evidence, with vertical slices, explicit decisions, and verification criteria.

MITAuto-check passedAgent Workflows

Install Planning

skills CLI
$ npx skills add mblode/agent-skills --skill planning -a claude-code

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

GitHub CLI
$ gh skill install mblode/agent-skills planning --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/mblode/agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/planning .claude/skills/planning && 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
planning
GitHub stars
143
Token cost
~1.3k tokens
SKILL.md length
670 words
Files
10 (incl. references)
Skills in repo
28
Repo updated
First seen
Licence
MIT

At a glance

Creates and reviews executable implementation plans grounded in repository evidence, with vertical slices, explicit decisions, and verification criteria.

  • Works in 5 steps: Identify the requested outcome and… → Inspect the modules, tests, and… → Choose the smallest vertical slice that… → …
  • Asked to plan this feature
  • SKILL.md covers References, Workflow, Plan contract and Review completion, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Planning is an agent skill from mblode/agent-skills. Creates and reviews executable implementation plans grounded in repository evidence, with vertical slices, explicit decisions, and verification criteria. Use when asked to "plan this feature", "stress-test this plan", "grill me", or "split this into tickets". For architecture use codebase-architecture; for code review use tidy.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including reference files (for example `evals/evals.json`, `references/claim-verification.md` and `references/decision-briefs.md`).

It sits in Agent Workflows, covering Planning, Load testing and Requirements gathering. The repository describes itself as: Nobody ships AI slop on purpose. These skills make sure you don’t. The licence is MIT.

When your agent uses it

  • Asked to plan this feature
  • Stress-test this plan
  • Split this into tickets

Example prompts

  • “plan this feature”
  • “stress-test this plan”
  • “grill me”
  • “/planning”

Workflow steps

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

  1. Identify the requested outcome and authoritative plan path. Use the host's plan file where one exists. A durable handoff goes at the…
  2. Inspect the modules, tests, and decisions that constrain this change. Resolve questions the repository answers yourself. Ask only when an…
  3. Choose the smallest vertical slice that exercises the real boundary. Name the existing code or platform capability it extends. A new…
  4. Write the plan with the contract below. Review the consequential claims once against the rubric; fix evidenced gaps directly. Interview…
  5. Return the plan path, unresolved decisions, and verification limits. Use the host's approval mechanism when its mode requires it. Do not…

What it can do on your machine

Read from SKILL.md and the folder at commit cef4cfa. 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

    No scripts in the folder and no shell commands in SKILL.md.

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

  • Network

    No URLs in SKILL.md.

    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

Planning loads about 1.3k tokens when it runs, and up to ~12k if it reads all its reference files. Until then it costs about 85 tokens; SKILL.md has 670 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~85
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~12k

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 mblode/agent-skills at commit cef4cfa, republished under its MIT licence (© mblode). 670 words, ~1,344 tokens.

Download SKILL.mdSave it as .claude/skills/planning/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.
name
planning
description
Creates and reviews executable implementation plans grounded in repository evidence, with vertical slices, explicit decisions, and verification criteria. Use when asked to "plan this feature", "stress-test this plan", "grill me", or "split this into tickets". For architecture use codebase-architecture; for code review use tidy.

Planning

Produce an executable plan, or strengthen an existing one. Planning alone produces no implementation edits. When the user asks to plan and implement, finish the plan and continue within the host's active mode and authorization.

  • Create: no plan exists; ground the approach in the repository and write the plan.
  • Review: a plan exists; verify its consequential claims and resolve concrete gaps in the file.
  • Interview: the user asks to be grilled or interviewed; explore decisions interactively.
  • Split: multiple independently deliverable outcomes need tickets with native dependency links.

For architecture contracts use codebase-architecture; for code findings use tidy.

References

FileRead when
references/decision-briefs.mdPresenting a consequential decision to the human: measuring options, previews, recording the answer
references/interrogation-protocol.mdChoosing which question to ask about an unresolved choice, or the user requested an interview
references/doc-grounding.mdADRs, specifications, or library docs constrain the approach
references/handoff-plans.mdAnother session or person will execute the plan
references/plan-quality-rubric.mdReviewing completeness, feasibility, scope, testability, risk, and assumptions
references/questioning-framework.mdA review gap needs a focused user question
references/claim-verification.mdA plan claim can be checked against code or documentation
references/splitting.mdDecomposing work into executable tickets

Workflow

  1. Identify the requested outcome and authoritative plan path. Use the host's plan file where one exists. A durable handoff goes at the project path, default docs/plans/<slug>.md; name which copy is authoritative.
  2. Inspect the modules, tests, and decisions that constrain this change. Resolve questions the repository answers yourself. Ask only when an unresolved choice materially changes scope, behavior, or a hard-to-reverse action. Routine assumptions belong in the draft. Before asking, measure the options and name what would flip your recommendation; when that hinge is a fact only the human has, ask about it directly (references/decision-briefs.md).
  3. Choose the smallest vertical slice that exercises the real boundary. Name the existing code or platform capability it extends. A new dependency or abstraction needs a current requirement the existing mechanism cannot satisfy.
  4. Write the plan with the contract below. Review the consequential claims once against the rubric; fix evidenced gaps directly. Interview mode can explore competing approaches, but has no minimum question count.
  5. Return the plan path, unresolved decisions, and verification limits. Use the host's approval mechanism when its mode requires it. Do not add a second approval question for the plan's own review.
Show full SKILL.md (290 more words)Show less

Plan contract

Include only sections this change needs:

  • Outcome: triggering problem, intended behavior, and acceptance criteria.
  • Approach: chosen slice, affected files or interfaces, and migration order where applicable.
  • Decisions: a decision log: question, choice, who decided and when, measured evidence per option, and what would flip it; assumptions that remain unverified.
  • Boundaries: exclusions only where an adjacent change would plausibly be mistaken for scope.
  • Verification: a command, test scenario, or observation tied to each material acceptance criterion, including expected failure behavior.
  • Recovery: rollback or recovery for migrations and irreversible writes.

A handoff is self-contained. Replace "as discussed" with the decision. Preserve user corrections in the file, not just the chat. Split tickets by shippable outcome, not database/backend/frontend layers.

Review completion

Resolve gaps supported by code, the task, or operational constraints. Do not add speculative requirements to improve a self-score. Scores are optional unless requested; when used, mark unverified claims and explain residual gaps rather than iterating until every cell says 5/5.

Repeat review only after a substantive edit or new evidence. A user decision that remains unanswered is recorded at the affected step; continue independent work. If the user says to skip questions, draft from available evidence and label the assumptions.

Gotchas

  • A plan in ~/.claude/plans/ is not available to other checkouts or CI. Durable handoffs need a project artifact.
  • A bare "run tests" step does not establish the changed behavior. Name the acceptance scenario and expected result.
  • Publishing slices without native blocker relations leaves the execution queue unaware of dependencies.
  • A plan written for a prior revision can name moved files. Verify consequential paths and interfaces against the current checkout.

Maintenance only: evals/evals.json contains regression scenarios for changes to this skill; it does not load during a user task.

© mblode, 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 9 other files (references) in skills/planning of mblode/agent-skills.

  • SKILL.md
  • evals/evals.json
  • references/claim-verification.md
  • references/decision-briefs.md
  • references/doc-grounding.md
  • references/handoff-plans.md
  • references/interrogation-protocol.md
  • references/plan-quality-rubric.md
  • references/questioning-framework.md
  • references/splitting.md

Open the folder on GitHubat commit cef4cfa

Compare with similar skills

Planning 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.

Planning compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Planning this skillmblode/agent-skills143—~1.3kAutomated safety check: PassMIT
Interview Meaddyosmani/agent-skills103k6 repos~3.8kAutomated safety check: PassMIT
Grillingpietheinstrengholt/rssmonster56432 repos~510Automated safety check: PassMIT
Brainstorming Before BuildingjnMetaCode/superpowers-zh8.3k—~1.8kAutomated safety check: PassMIT
ULW Plan Workflowcode-yeongyu/oh-my-openagent70k—~3.9kAutomated safety check: PassCustom licence
CE BrainstormEveryInc/compound-engineering-plugin25k—~1.9kAutomated safety check: PassMIT

Similar skills

  • Interview Me

    addyosmani/agent-skills

    Asks one question at a time, each with a best guess attached, until the agent is about 95 percent sure what you really want, before any plan, spec or code.

    103k GitHub starsUsed in 6 repos~3.8k tokens
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  • Grilling

    pietheinstrengholt/rssmonster

    Grill the user relentlessly about a plan, decision, or idea.

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  • Brainstorming Before Building

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    Agent WorkflowsAuto-check passed
  • ULW Plan Workflow

    code-yeongyu/oh-my-openagent

    Explore-first planning that turns a vague or large request into one decision-complete work plan, written only after your approval and executed by a separate worker.

    70k GitHub stars~3.9k tokensUpdated today
    Agent WorkflowsAuto-check passed
  • CE Brainstorm

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    Turns a vague or ambitious feature idea into a requirements-only plan through dialogue with you, sized to the work, before any code is written.

    25k GitHub stars~1.9k tokensUpdated today
    Agent WorkflowsAuto-check passed
  • Ask Navigator

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    Charts a foggy effort into a map of decision tickets on the repo's issue tracker and works through them one per session, producing decisions rather than deliverables.

    40k GitHub stars~4.1k tokensUpdated today
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Categories

Questions about Planning

What does Planning do?

Creates and reviews executable implementation plans grounded in repository evidence, with vertical slices, explicit decisions, and verification criteria. Planning is an agent skill from mblode/agent-skills. Creates and reviews executable implementation plans grounded in repository evidence, with vertical slices, explicit decisions, and verification criteria.

When should I use Planning?

Planning fits situations like: asked to plan this feature; stress-test this plan; split this into tickets.

How do I install Planning in Claude Code?

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

How do I install Planning in Codex?

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

Can I use Planning 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 mblode/agent-skills --skill planning -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/planning, .gemini/skills/planning, .github/skills/planning and .opencode/skills/planning in your project.

What does Planning need to run?

SKILL.md names no scripts, command-line tools or credentials: Planning is instructions for the agent only.

Does Planning access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Planning 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 Planning use?

Planning 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 Planning use?

About 1.3k tokens (SKILL.md is roughly 5.4k 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 11k tokens, read only when the agent opens those files.

What are the alternatives to Planning?

Skills that share tags, products or a category with Planning: Interview Me (addyosmani/agent-skills, 103k stars), Grilling (pietheinstrengholt/rssmonster, 564 stars), Brainstorming Before Building (jnMetaCode/superpowers-zh, 8.3k stars) and ULW Plan Workflow (code-yeongyu/oh-my-openagent, 70k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Planning?

mblode (a GitHub user) maintains it in mblode/agent-skills, which has 143 GitHub stars. The repository holds 28 skills in this directory. The repository was last updated on October 6, 2026.

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