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.
npx agentmods add skills/bradymck/claude-code-harness/prdnpx skills add Bradymck/claude-code-harness --skill prdgit clone --depth 1 https://github.com/Bradymck/claude-code-harnessWrote 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.
[](https://agentmods.dev/skills/bradymck/claude-code-harness/prd)<a href="https://agentmods.dev/skills/bradymck/claude-code-harness/prd"><img src="https://agentmods.dev/badge/skills/bradymck/claude-code-harness/prd.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00060 | $0.01678 |
| Opus 5 | $0.00030 | $0.00839 |
| Sonnet 5 | $0.00012 | $0.00336 |
| Haiku 4.5 | $0.00006 | $0.00168 |
Grade A, and why
prd 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 3d 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.
This is a copy
94% identical to prd — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 242 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PRD Generator
Create detailed Product Requirements Documents that are clear, actionable, and suitable for implementation.
The Job
- Receive a feature description from the user
- Ask 3-5 essential clarifying questions (with lettered options)
- Generate a structured PRD based on answers
- Save to
tasks/prd-[feature-name].md
Important: Do NOT start implementing. Just create the PRD.
Step 1: Clarifying Questions
Ask only critical questions where the initial prompt is ambiguous. Focus on:
- Problem/Goal: What problem does this solve?
- Core Functionality: What are the key actions?
- Scope/Boundaries: What should it NOT do?
- Success Criteria: How do we know it's done?
Format Questions Like This:
1. What is the primary goal of this feature?
A. Improve user onboarding experience
B. Increase user retention
C. Reduce support burden
D. Other: [please specify]
2. Who is the target user?
A. New users only
B. Existing users only
C. All users
D. Admin users only
3. What is the scope?
A. Minimal viable version
B. Full-featured implementation
C. Just the backend/API
D. Just the UI
This lets users respond with "1A, 2C, 3B" for quick iteration.
Step 2: PRD Structure
Generate the PRD with these sections:
1. Introduction/Overview
Brief description of the feature and the problem it solves.
2. Goals
Specific, measurable objectives (bullet list).
3. User Stories
Each story needs:
- Title: Short descriptive name
- Description: "As a [user], I want [feature] so that [benefit]"
- Acceptance Criteria: Verifiable checklist of what "done" means
Each story should be small enough to implement in one focused session.
Format:
### US-001: [Title]
**Description:** As a [user], I want [feature] so that [benefit].
**Acceptance Criteria:**
- [ ] Specific verifiable criterion
- [ ] Another criterion
- [ ] Typecheck/lint passes
- [ ] **[UI stories only]** Verify in browser using dev-browser skill
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.
- 3d ago First seen · 242 lines · 60 tokens per session scan A 3fd212844a0d
prd is a skill published in the GitHub repository Bradymck/claude-code-harness (2 stars, last pushed 2mo ago), licensed MIT. It adds 60 tokens to every session and 1,678 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to prd, differing in 2 lines, and is treated as a copy.
Other skills, from other repositories
hive.chart-creation-foundations
Required reading whenever any chart tool is available. Teaches the one-tool embedding contract (call chartrender → live chart appears in chat AND a downloadable PNG lands in the queen session dir), the ECharts (data viz) vs Mermaid (structural diagrams) decision, the BI/financial-grade aesthetic baseline (no…
browser-edge-cases
SOP for debugging browser automation failures on complex websites. Use when browser tools fail on specific sites like LinkedIn, Twitter/X, SPAs, or sites with Shadow DOM.
openai-whisper-api
Transcribe audio via OpenAI Audio Transcriptions API (Whisper).
chat-complex-documents
Chat with and search your complex documents — ask questions, extract tables and fields, and get answers grounded in the source. Connects the hosted Unstructured Transform MCP server to parse, structure, and enrich PDFs, Word/Excel/PowerPoint, images, scanned files, emails, and 60+ other formats into clean, AI-ready…
agentic-loop-skill
Autonomous decision loop with reflection and iteration.
perf-code-paths
Use when mapping code paths, entrypoints, and likely hot files before profiling.