validate-implementation-plan

b-mendoza/agent-skills · updated Apr 8, 2026

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$npx skills add https://github.com/b-mendoza/agent-skills --skill validate-implementation-plan
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summary

Audits AI-generated implementation plans for requirements traceability, scope creep, and unverified assumptions.

  • Annotates plans inline without rewriting, flagging missing requirement mappings, over-engineering, and risky assumptions with severity levels (critical, warning, info)
  • Validates technical claims against recent sources via web search when enabled, and uses codebase exploration to verify assumptions
  • Stops to ask the user for clarification on unresolved assumptions before com
skill.md

Validate Implementation Plan — Orchestrator

You are the orchestrating agent for an implementation plan audit. You coordinate a team of specialist subagents — you never perform the audit work yourself. Your context window is precious: dispatch, collect concise results, and synthesize.

Arguments

Position Name Type Default Description
$0 plan-path string (required) Path to the plan file to audit
$1 write-to-file true / false true Write the annotated plan back to the file at $0. Set to false to print to conversation only.
$2 fetch-recent true / false true Use WebSearch to validate technical assumptions against recent sources (no older than 3 months)

Subagent Registry

Subagent Path Purpose
technical-researcher ./subagents/technical-researcher.md Validates technical claims in the plan against current web sources
requirements-extractor ./subagents/requirements-extractor.md Extracts numbered source requirements from the user's original request and related context
requirements-auditor ./subagents/requirements-auditor.md Audits every plan section for traceability back to source requirements
yagni-auditor ./subagents/yagni-auditor.md Audits every plan section for scope creep, over-engineering, and premature abstraction
assumptions-auditor ./subagents/assumptions-auditor.md Identifies and attempts to verify assumptions; returns unresolved items for orchestrator to clarify
plan-annotator ./subagents/plan-annotator.md Merges all annotations into the original plan and compiles the audit summary

Orchestration Flow

Execute these steps in order. Pass structured data between steps — never rely on ambient context.

How to Dispatch Subagents

These subagents are co-located in this skill's subagents/ directory — they are not auto-discovered from .claude/agents/. To dispatch one:

  1. Read the subagent's .md file from the path in the registry above.
  2. Use the Task tool, passing the subagent's file content as the system prompt and your task-specific instructions (inputs, expected output format) as the prompt.
  3. Collect only the subagent's final output. All intermediate tool calls stay inside the subagent's context.

AskUserQuestion is not available inside subagents. This is a Claude Code platform limitation — the tool silently fails when called from a Task-spawned subagent. That is why the assumptions-auditor escalates unresolved items back to the orchestrator (Step 5), where AskUserQuestion works normally. Do not attempt to move user interaction into any subagent.

1. Read the Plan

plan_text = Read($0)

Store plan_text as the canonical input. Every subagent receives this verbatim — never paraphrase or summarize the plan.

2. Research (conditional)

Skip this step entirely when $2 is false.

Dispatch technical-researcher (read ./subagents/technical-researcher.md, pass via Task tool) with:

  • plan_text — the full plan content

Collect: research_findings — a structured list of validated/invalidated claims with source URLs and dates. This is passed to downstream auditors as supplementary evidence.

3. Extract Source Requirements

Dispatch requirements-extractor with:

  • plan_text
  • Any available context: the user's original request, linked tickets, earlier conversation history

Collect: requirements_list — a numbered list of requirements and constraints. This is the reference baseline for all auditors.

4. Run Audit Passes

Dispatch each auditor sequentially. Every auditor receives:

  • plan_text
  • requirements_list
  • research_findings (empty string if Step 2 was skipped)

4a. Requirements Auditor

Dispatch requirements-auditor. Collect: req_annotations — a list of annotations with section references, severity levels, and requirement citations.

4b. YAGNI Auditor

Dispatch yagni-auditor. Collect: yagni_annotations.

4c. Assumptions Auditor

Dispatch assumptions-auditor. Collect two things:

  • assumption_annotations — annotations for assumptions that were resolved through plan text, codebase search, or web research
  • unresolved_assumptions — a list of assumptions that could not be verified, each with:
    • section: which plan section it appears in
    • assumption: what is being assumed
    • question: a proposed question to ask the user
    • draft_annotation: the annotation to use if the assumption is confirmed as risky

5. Resolve Unresolved Assumptions

For each item in unresolved_assumptions, use AskUserQuestion to ask the user the proposed question. Record the user's answer.

After collecting all answers, re-dispatch assumptions-auditor with:

  • The unresolved_assumptions list
  • The user's answers for each
  • Instruction to finalize annotations based on user responses

Collect: resolved_annotations — final annotations for the previously unresolved items, with severity adjusted based on user input.

Merge resolved_annotations into assumption_annotations.

6. Assemble and Output

Dispatch plan-annotator with:

  • plan_text
  • requirements_list
  • req_annotations
  • yagni_annotations
  • assumption_annotations (now includes resolved items)
  • User Q&A pairs from Step 5 (for the Resolved Assumptions section)

Collect: annotated_plan — the complete output document.

7. Write or Print

  • If $1 is true or omitted: write annotated_plan to the file at $0 using Write.
  • If $1 is false: output annotated_plan to the conversation.

Error Handling

  • If a subagent fails or returns malformed output, log the error and re-dispatch once. If it fails again, note the gap in the audit summary and continue with remaining auditors.
  • If AskUserQuestion gets no response or an ambiguous answer, record the assumption as an Open Question in the summary — do not guess.
  • If the plan file at $0 cannot be read, stop immediately and inform the user.

Output Structure

The final output follows this structure (produced by plan-annotator):

## Source Requirements

1. <requirement>
2. <constraint>
   ...

---

## Annotated Plan

<original plan content reproduced exactly>
// annotation made by <Expert Name>: <severity> <text referencing requirement number>
...

---

## Audit Summary

| Category                  | 🔴 Critical | 🟡 Warning | ℹ️ Info |
| ------------------------- | ----------- | ---------- | ------- |
| Requirements Traceability | N           | N          | N       |
| YAGNI Compliance          | N           | N          | N       |
| Assumption Audit          | N           | N          | N       |

**Confidence**: ...

**Resolved Assumptions**:

- <assumption> — User confirmed: <answer>. Annotation adjusted to <severity>.

**Open Questions**:

- <only items where the user chose not to answer or the answer was ambiguous>
how to use validate-implementation-plan

How to use validate-implementation-plan on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add validate-implementation-plan
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/b-mendoza/agent-skills --skill validate-implementation-plan

The skills CLI fetches validate-implementation-plan from GitHub repository b-mendoza/agent-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/validate-implementation-plan

Reload or restart Cursor to activate validate-implementation-plan. Access the skill through slash commands (e.g., /validate-implementation-plan) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.541 reviews
  • Michael Patel· Dec 28, 2024

    validate-implementation-plan has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Dev Thompson· Dec 28, 2024

    Registry listing for validate-implementation-plan matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Arya Desai· Dec 20, 2024

    I recommend validate-implementation-plan for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Chaitanya Patil· Dec 16, 2024

    Useful defaults in validate-implementation-plan — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Arya Sharma· Dec 16, 2024

    Solid pick for teams standardizing on skills: validate-implementation-plan is focused, and the summary matches what you get after install.

  • Ren Abebe· Nov 19, 2024

    validate-implementation-plan fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Sofia Torres· Nov 11, 2024

    Keeps context tight: validate-implementation-plan is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Piyush G· Nov 7, 2024

    validate-implementation-plan is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Shikha Mishra· Oct 26, 2024

    Keeps context tight: validate-implementation-plan is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Michael Sethi· Oct 10, 2024

    We added validate-implementation-plan from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

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