planning-doc-generator

planning-doc-generator is a skill for Claude Code from matteocervelli/llms. It costs 28 tokens per session (1,212 once invoked), scanned A, original, MIT.

A tool that turns structured project information into a Markdown assessment document with purpose, stakeholders, scope, and a go-or-no-go decision table.

In plain words
What is it for?
Use it to create project assessments, document the project vision and scope, analyze stakeholders, and record a go-or-no-go decision.
Why use it?
It helps teams turn planning data into a consistent document for evaluating a project and aligning the people involved.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it to create project assessments, document the project vision and scope…

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/matteocervelli/llms/planning-doc-generator
Install

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.

Any agent
npx skills add matteocervelli/llms --skill planning-doc-generator
Clone the repo
git clone --depth 1 https://github.com/matteocervelli/llms

Made for: Claude Code.

Wrote 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.

agentmods badge for planning-doc-generator

README.md
[![agentmods](https://agentmods.dev/badge/skills/matteocervelli/llms/planning-doc-generator.svg)](https://agentmods.dev/skills/matteocervelli/llms/planning-doc-generator)
Your own site
<a href="https://agentmods.dev/skills/matteocervelli/llms/planning-doc-generator"><img src="https://agentmods.dev/badge/skills/matteocervelli/llms/planning-doc-generator.svg" alt="Measured on agentmods" height="20"></a>
Per session 28 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,212 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00028 $0.01212
Opus 5 $0.00014 $0.00606
Sonnet 5 $0.00006 $0.00242
Haiku 4.5 $0.00003 $0.00121

Measured 5d ago against content hash 354d3ab96990, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

planning-doc-generator 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 5d 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.

.archive/claude-v1/skills/planning-doc-generator/SKILL.md · 186 lines

How it starts

The opening of the file, as written. The whole thing — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Planning Document Generator Skill

Purpose

Generate structured assessment documents from JSON configuration. Converts project planning data into markdown assessment reports with purpose, stakeholder, and scope analysis plus a GO/NO-GO decision framework.

When to Use

  • Creating project assessment documents
  • Generating planning documentation from structured data
  • Building evaluation reports with decision matrices
  • Documenting project vision and scope
  • Creating stakeholder alignment assessments
  • Generating baseline project documentation

Input: JSON Format

The skill expects JSON input with the following structure:

{
  "project_name": "Project Name",
  "date": "2025-11-03",
  "why": {
    "exists": "Why does this project exist?",
    "problem": "What problem does it solve?",
    "vision": "What is the desired outcome?"
  },
  "who": {
    "stakeholders": "List of key stakeholders",
    "decision_makers": "Who decides",
    "executors": "Who does the work",
    "concerns": "Their priorities and concerns"
  },
  "what": {
    "building": "What are we building/changing?",
    "features": "Key features and components",
    "out_of_scope": "What is out of scope",
    "success_criteria": "Definition of success"
  },
  "go_no_go": {
    "purpose_clarity": "✓|⚠|✗",
    "stakeholder_alignment": "✓|⚠|✗",
    "scope_definition": "✓|⚠|✗",
    "resource_availability": "✓|⚠|✗",
    "timeline_feasibility": "✓|⚠|✗",
    "risk_assessment": "✓|⚠|✗",
    "success_metrics": "✓|⚠|✗"
  },
  "decision": "GO|CONDITIONAL|NO-GO",
  "rationale": "Explanation of decision"
}

Template Filling Process

  1. Load templates/assessment-template.md
  2. Replace all {PLACEHOLDER} values with JSON data
  3. Calculate coverage: Count non-empty answers ÷ 17 questions
  4. Insert status indicators (✓/⚠/✗) from GO/NO-GO section
  5. Generate markdown with formatted decision matrix
  6. Validate all sections populated with content (no {ANSWER} remaining)

Coverage Calculation

Read the full file on GitHub · 186 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 5d ago First seen · 186 lines · 28 tokens per session scan A 354d3ab96990

Subscribe to this mod's changes

planning-doc-generator is a skill published in the GitHub repository matteocervelli/llms (25 stars, last pushed 3mo ago), licensed MIT. It adds 28 tokens to every session and 1,212 once invoked, about $0.0001 per session on Opus 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 2026-09-01.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens