CCPM Project Management
automazeio/ccpm
Runs a spec-driven workflow from PRD to epic to GitHub issues to parallel agents, with status, standup and blocked-work reports from bundled scripts.
Discover product requirements from human stakeholders — map who to talk to, ask questions that surface hidden assumptions, detect gaps in real time, resolve conflicts, and translate conversations…
Install Product Discovery
$ npx skills add magnus919/agent-skills --skill product-discovery -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install magnus919/agent-skills product-discovery --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/magnus919/agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/product-discovery .claude/skills/product-discovery && rm -rf skills-srcUse ~/.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/
Install the "product-discovery" agent skill from https://github.com/magnus919/agent-skills/tree/main/product-discovery into .claude/skills/product-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-discovery", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/magnus919/agent-skills/tree/main/product-discoveryType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add magnus919/agent-skills --skill product-discovery -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install magnus919/agent-skills product-discovery --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/magnus919/agent-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/product-discovery .agents/skills/product-discovery && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "product-discovery" agent skill from https://github.com/magnus919/agent-skills/tree/main/product-discovery into .agents/skills/product-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-discovery", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add magnus919/agent-skills --skill product-discovery -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install magnus919/agent-skills product-discovery --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/magnus919/agent-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/product-discovery .cursor/skills/product-discovery && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "product-discovery" agent skill from https://github.com/magnus919/agent-skills/tree/main/product-discovery into .cursor/skills/product-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-discovery", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/magnus919/agent-skills.git --path product-discovery--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add magnus919/agent-skills --skill product-discovery -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install magnus919/agent-skills product-discovery --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/magnus919/agent-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/product-discovery .gemini/skills/product-discovery && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "product-discovery" agent skill from https://github.com/magnus919/agent-skills/tree/main/product-discovery into .gemini/skills/product-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-discovery", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install magnus919/agent-skills product-discoveryInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add magnus919/agent-skills --skill product-discovery -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/magnus919/agent-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/product-discovery .github/skills/product-discovery && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "product-discovery" agent skill from https://github.com/magnus919/agent-skills/tree/main/product-discovery into .github/skills/product-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-discovery", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add magnus919/agent-skills --skill product-discovery -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install magnus919/agent-skills product-discovery --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/magnus919/agent-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/product-discovery .opencode/skills/product-discovery && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "product-discovery" agent skill from https://github.com/magnus919/agent-skills/tree/main/product-discovery into .opencode/skills/product-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-discovery", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
product-discovery- GitHub stars
- 115
- Token cost
- ~2.2k tokens
- SKILL.md length
- 873 words
- Files
- 21 (incl. references)
- Skills in repo
- 131
- Repo updated
- First seen
- Licence
- MIT
At a glance
Discover product requirements from human stakeholders — map who to talk to, ask questions that surface hidden assumptions, detect gaps in real time, resolve conflicts, and translate conversations…
- Personal-life discovery (daily-life-discovery)
- SKILL.md covers Pipeline: Phase 0 — Discovery, Quick Start — Where to Enter, Artifact-first review and When not to use, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- General research without product requirements (research-methodology)
What it does
Product Discovery is an agent skill from magnus919/agent-skills. Discover product requirements from human stakeholders — map who to talk to, ask questions that surface hidden assumptions, detect gaps in real time, resolve conflicts, and translate conversations into structured SDD specs. Phase 0 upstream of Spec-Driven Development. Also grill a PRD, interrogate a proposal, poke holes in a spec, or interview its author about an existing draft, one consequential question at a time. Do not use for personal-life discovery (daily-life-discovery), general research without product…
Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 23 other files, including reference files (for example `README.md`, `evals/artifact-first-rubric-review.md` and `evals/artifact-first-run.json`). Compatibility notes: Agent-agnostic — works with any agent supporting a spec-driven or requirements pipeline.
It sits in Product & Project Management, covering PRD writing, Experimental design and Spec-driven development. The repository describes itself as: Curated collection of AI agent skills for Hermes and other agent frameworks. The licence is MIT.
When your agent uses it
- Personal-life discovery (daily-life-discovery)
- General research without product requirements (research-methodology)
- Implementation planning
Example prompts
- “/product-discovery”
Requirements
- Compatibility (from SKILL.md): Agent-agnostic — works with any agent supporting a spec-driven or requirements pipeline.
What it can do on your machine
Read from SKILL.md and the folder at commit 22b4723. 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.
Compatibility
Agent-agnostic — works with any agent supporting a spec-driven or requirements pipeline.
From compatibility in the SKILL.md frontmatter.
Context cost
Product Discovery loads about 2.2k tokens when it runs, and up to ~12k if it reads all its reference files. Until then it costs about 149 tokens; SKILL.md has 873 words of instructions outside code blocks.
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 magnus919/agent-skills at commit 22b4723, republished under its MIT licence (© magnus919). 873 words, ~2,193 tokens.
Download SKILL.mdSave it as
.claude/skills/product-discovery/SKILL.md (or your agent's skills folder). This skill also uses 20 other files; get the full folder from GitHub.- name
- product-discovery
- description
- Discover product requirements from human stakeholders — map who to talk to, ask questions that surface hidden assumptions, detect gaps in real time, resolve conflicts, and translate conversations into structured SDD specs. Phase 0 upstream of Spec-Driven Development. Also grill a PRD, interrogate a proposal, poke holes in a spec, or interview its author about an existing draft, one consequential question at a time. Do not use for personal-life discovery (daily-life-discovery), general research without product requirements (research-methodology), or implementation planning.
- compatibility
- Agent-agnostic — works with any agent supporting a spec-driven or requirements pipeline.
- license
- MIT
Product Discovery — Stakeholder Map
For an existing draft, use the artifact-first entry below. For a new discovery effort, begin with stakeholder mapping:
| Reference | Load when | File |
|---|---|---|
| Stakeholder Mapping & Sequencing | You need to decide who to interview and in what order | references/stakeholder-mapping.md |
| Interview Protocol Design | You're designing a question stack for a specific stakeholder type | references/question-patterns.md |
| Gap Detection Techniques | You're preparing to recognize what stakeholders don't say | references/gap-detection.md |
Pipeline: Phase 0 — Discovery
RAW NEED → [MAP] → [INTERVIEW] → [SYNTHESIZE] → [DISTILL] → [VALIDATE] → SPEC.md
| | | | |
Who to What to Resolve Convert to Stakeholder
talk to ask conflicts structured reviewLoad the reference for the phase you're entering.
Core principles
- Closed questions confirm what you already think; open questions discover what you didn't know to ask. If the answer can be "yes" or "no," you're validating, not discovering.
- Knowledge holders come first; authority holders validate — they don't originate. The person who knows the problem is not the same person who approves the budget.
- Conflicts are almost never about what they appear to be. Surface disagreements are proxies for unstated differences in assumptions, risk tolerance, or incentives.
- Every weasel word represents a gap. "Probably," "ideally," "eventually" — each is a known issue the stakeholder hasn't committed to addressing.
Quick Start — Where to Enter
| You have this | Start here |
|---|---|
| A PRD, brief, or spec to grill with its author | Load references/artifact-first-interview.md — ask one consequential question at a time, then patch only affected passages |
| A vague idea or problem space | Load references/stakeholder-mapping.md — identify who to interview |
| An interview scheduled with no protocol | Load references/question-patterns.md and references/gap-detection.md — design your question stack |
| Raw interview notes from one or more sessions | Load references/transcript-to-spec.md — distill into structured spec components |
| A draft spec that needs stakeholder verification | Load references/transcript-to-spec.md (Interpretation Audit Trail section) — run the validation loop |
| Stakeholders who disagree on requirements | Load references/conflict-resolution.md — classify and resolve before spec |
| Limited time with a stakeholder | Load references/time-constrained-discovery.md — maximize signal in minimal time |
| An AI agent conducting interviews | Load references/ai-conducted-discovery.md — account for sycophancy and trust dynamics |
Done with discovery? Use product-methodology to choose scope, then product-design-and-ux to define user-facing behavior. Jump to the Is Discovery Complete? checklist at the bottom.
Artifact-first review
When the user brings a draft to interrogate, load artifact-first interviewing. Read the artifact before asking; choose one decision-bearing question, wait for the answer, then adapt. Reuse the gap register for assumptions and unresolved conflicts, and the interpretation log for decisions and patch provenance. Stop when the user stops, the agreed question budget expires, or no consequential unresolved decision remains. Return a targeted proposed patch and explicitly unverified gaps. This bounded review does not satisfy the full-discovery checklist below.
When not to use
Route personal routines and life priorities to daily-life-discovery, general research plans to research-methodology, and execution sequencing for settled requirements to implementation-planning. General stakeholder research for a product still uses this skill’s existing MAP/INTERVIEW workflow; do not force it into draft review.
Trigger Conditions
Load this skill when:
- You want to grill a PRD, poke holes in a proposal, or be interviewed about a draft
- You're starting product discovery for a new feature or project
- You have a vague idea that needs to become a structured specification
- You need to interview stakeholders but don't have a protocol
- You have raw interview notes that need to become a SPEC.md
- You're about to enter Phase 1 (SPECIFY) of SDD and need upstream input
- You're evaluating whether you've done enough discovery work
Show full SKILL.md (330 more words)Show less
Loading Guide
| Phase | Load When | File |
|---|---|---|
| MAP | You need to identify who to interview, in what order, and how to find the right stakeholders | references/stakeholder-mapping.md |
| INTERVIEW | You're about to conduct stakeholder interviews and need question patterns, gap detection, and conflict handling | references/question-patterns.md + references/gap-detection.md + references/conflict-resolution.md |
| SYNTHESIZE | You have raw interview notes and need to identify conflicts, risks, and gaps before distillation | references/conflict-resolution.md |
| DISTILL | You need to transform interview notes into structured SPEC.md with ACs, edge cases, and NFRs | references/transcript-to-spec.md |
| VALIDATE | You have a draft spec and need to verify interpretations with stakeholders | references/transcript-to-spec.md (Interpretation Audit Trail section) |
Cross-Cutting Concerns
These dimensions apply across all phases. Load when relevant:
| Concern | Load when | File |
|---|---|---|
| AI-conducted discovery | An AI agent is conducting discovery interviews | references/ai-conducted-discovery.md |
| Power dynamics | Stakeholders span multiple organizational levels; hierarchy may distort responses | references/power-dynamics.md |
| Time constraints | Stakeholder time is limited; need maximum signal extraction | references/time-constrained-discovery.md |
Templates
| Template | Pipeline Phase | Load when | File |
|---|---|---|---|
| Discovery Plan | MAP | You need to structure the full discovery effort — stakeholder map, interview schedule, timeline | templates/discovery-plan.md |
| Interview Guide | INTERVIEW | You need a structured question stack for an interview session | templates/interview-guide.md |
| Distillation Worksheet | DISTILL | You're transforming raw notes into structured spec components | templates/distillation-worksheet.md |
| Gap Register | SYNTHESIZE | You need to track unresolved gaps, deferred decisions, and open questions across interviews | templates/gap-register.md |
| Interpretation Log | DISTILL → VALIDATE | You need to track every translation from stakeholder language to spec language | templates/interpretation-log.md |
Quick Reference: Is Discovery Complete?
For full stakeholder discovery before handing off to SDD Phase 1 (SPECIFY), use this checklist. A stopped artifact-first review reports remaining gaps instead of declaring these complete:
- All stakeholder types interviewed (knowledge holders, authority holders, affected parties, implementation knowers)?
- At least 3 independent sources for every requirement?
- Abstract nouns decomposed into measurable thresholds?
- Conflicts resolved or documented with decision-maker identified?
- Edge cases extracted from stakeholder anecdotes?
- Every AC classified: SAID / IMPLIED / INTERPRETED / INFERRED?
- HIGH-risk interpretations identified and flagged for validation?
- Gaps, deferred decisions, and avoided topics documented?
- Stakeholder validation loop completed?
- Interpretation audit trail preserved for handoff?
© magnus919, 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 20 other files (references) in product-discovery of magnus919/agent-skills.
- SKILL.md
- README.md
- evals/artifact-first-rubric-review.md
- evals/artifact-first-run.json
- evals/artifact-first-validation.md
- evals/evals.json
- evals/trigger-queries.json
- references/ai-conducted-discovery.md
- references/artifact-first-interview.md
- references/conflict-resolution.md
- references/gap-detection.md
- references/power-dynamics.md
- references/question-patterns.md
- references/stakeholder-mapping.md
- references/time-constrained-discovery.md
- references/transcript-to-spec.md
- templates/discovery-plan.md
- templates/distillation-worksheet.md
- … and 3 more
Open the folder on GitHubat commit 22b4723
Compare with similar skills
Product Discovery 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Product Discovery this skillmagnus919/agent-skills | 115 | — | ~2.2k | Automated safety check: Pass | MIT | |
| CCPM Project Managementautomazeio/ccpm | 8.4k | — | ~1.1k | Automated safety check: Pass | MIT | |
| User Alignment and Agent-Ready PRDstryproduck/produck-skills | 511 | — | ~5.3k | Automated safety check: Pass | Apache-2.0 | |
| Product Requirements Documentowainlewis/blueprint | 412 | — | ~766 | Automated safety check: Pass | MIT | |
| Spec Driven Evaltech-leads-club/agent-skills | 7k | — | ~8.8k | Automated safety check: Pass | CC-BY-4.0 | |
| Spec Driven Loopsickn33/agentic-awesome-skills | 47k | 1 repos | ~3.4k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Product Discovery
What does Product Discovery do?
Discover product requirements from human stakeholders — map who to talk to, ask questions that surface hidden assumptions, detect gaps in real time, resolve conflicts, and translate conversations…. Product Discovery is an agent skill from magnus919/agent-skills. Discover product requirements from human stakeholders — map who to talk to, ask questions that surface hidden assumptions, detect gaps in real time, resolve conflicts, and translate conversations into structured SDD specs.
When should I use Product Discovery?
Product Discovery fits situations like: personal-life discovery (daily-life-discovery); general research without product requirements (research-methodology); implementation planning.
How do I install Product Discovery in Claude Code?
Run `npx skills add magnus919/agent-skills --skill product-discovery -a claude-code`. Or copy the skill folder (product-discovery in magnus919/agent-skills) into .claude/skills/product-discovery in your project. Claude Code loads it when a task matches its description.
How do I install Product Discovery in Codex?
Run `npx skills add magnus919/agent-skills --skill product-discovery -a codex`. Or copy the skill folder (product-discovery in magnus919/agent-skills) into .agents/skills/product-discovery in your project. Codex loads it when a task matches its description.
Can I use Product Discovery 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 magnus919/agent-skills --skill product-discovery -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/product-discovery, .gemini/skills/product-discovery, .github/skills/product-discovery and .opencode/skills/product-discovery in your project.
What does Product Discovery need to run?
SKILL.md names no scripts, command-line tools or credentials: Product Discovery is instructions for the agent only. Compatibility (from SKILL.md): Agent-agnostic — works with any agent supporting a spec-driven or requirements pipeline..
Does Product Discovery 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 Product Discovery 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 Product Discovery use?
Product Discovery is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Product Discovery use?
About 2.2k tokens (SKILL.md is roughly 8.8k 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 9.9k tokens, read only when the agent opens those files.
What are the alternatives to Product Discovery?
Skills that share tags, products or a category with Product Discovery: CCPM Project Management (automazeio/ccpm, 8.4k stars), User Alignment and Agent-Ready PRDs (tryproduck/produck-skills, 511 stars), Product Requirements Document (owainlewis/blueprint, 412 stars) and Spec Driven Eval (tech-leads-club/agent-skills, 7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Product Discovery?
magnus919 (a GitHub user) maintains it in magnus919/agent-skills, which has 115 GitHub stars. The repository holds 131 skills in this directory. The repository was last updated on October 10, 2026.
Source: magnus919/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.