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.
Run an optional guided product-discovery interview and draft project-plan.md and build-plan.md only after the user is ready.
$ npx skills add aiblueprinthq/ai-blueprint --skill discovery -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aiblueprinthq/ai-blueprint 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/aiblueprinthq/ai-blueprint.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/discovery .claude/skills/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 "discovery" agent skill from https://github.com/aiblueprinthq/ai-blueprint/tree/main/.agents/skills/discovery into .claude/skills/discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "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/aiblueprinthq/ai-blueprint/tree/main/.agents/skills/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 aiblueprinthq/ai-blueprint --skill discovery -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aiblueprinthq/ai-blueprint discovery --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiblueprinthq/ai-blueprint.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/discovery .agents/skills/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 "discovery" agent skill from https://github.com/aiblueprinthq/ai-blueprint/tree/main/.agents/skills/discovery into .agents/skills/discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "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 aiblueprinthq/ai-blueprint --skill discovery -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aiblueprinthq/ai-blueprint discovery --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiblueprinthq/ai-blueprint.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/discovery .cursor/skills/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 "discovery" agent skill from https://github.com/aiblueprinthq/ai-blueprint/tree/main/.agents/skills/discovery into .cursor/skills/discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "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/aiblueprinthq/ai-blueprint.git --path .agents/skills/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 aiblueprinthq/ai-blueprint --skill discovery -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aiblueprinthq/ai-blueprint discovery --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiblueprinthq/ai-blueprint.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/discovery .gemini/skills/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 "discovery" agent skill from https://github.com/aiblueprinthq/ai-blueprint/tree/main/.agents/skills/discovery into .gemini/skills/discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "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 aiblueprinthq/ai-blueprint 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 aiblueprinthq/ai-blueprint --skill discovery -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aiblueprinthq/ai-blueprint.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/discovery .github/skills/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 "discovery" agent skill from https://github.com/aiblueprinthq/ai-blueprint/tree/main/.agents/skills/discovery into .github/skills/discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "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 aiblueprinthq/ai-blueprint --skill 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 aiblueprinthq/ai-blueprint discovery --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiblueprinthq/ai-blueprint.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/discovery .opencode/skills/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 "discovery" agent skill from https://github.com/aiblueprinthq/ai-blueprint/tree/main/.agents/skills/discovery into .opencode/skills/discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "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.
discoveryRun an optional guided product-discovery interview and draft project-plan.md and build-plan.md only after the user is ready.
Discovery is an agent skill from aiblueprinthq/ai-blueprint. Run an optional guided product-discovery interview and draft project-plan.md and build-plan.md only after the user is ready. Use for /discovery, guided planning, thinking through a new product, or deepening plans. Never require it before /overview.
Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).
It sits in Product & Project Management, covering Project management. The repository describes itself as: A file-backed, spec-driven AI coding workflow framework for building real software while staying in control. The licence is MIT.
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 96222b7. It shows what the files ask for, not the result of running them.
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.
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.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Discovery loads about 2.1k tokens when it runs. Until then it costs about 65 tokens; SKILL.md has 1,146 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.
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.
The full file from aiblueprinthq/ai-blueprint at commit 96222b7, republished under its MIT licence (© aiblueprinthq). 1,146 words, ~2,078 tokens.
.claude/skills/discovery/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Context reuse: Reuse any required file already loaded in project instructions or the current session. Read it again only if absent, changed, or exact current bytes or line references are needed.
First action: Before project inspection, preflight, or any other tool call,
publish running to blueprint/.state/run.json using the dashboard activity
contract in AGENTS.md.
Where this can sit in the workflow:
/onboard -> write the plans directly -> /overview
\
-> [discovery] -> review and approve plan drafts -> /overview/discovery is an optional planning partner, not a required workflow gate and
not a quick questionnaire. It can span as many turns as the project needs. Its
job is to help the user think through the product, preserve the depth and nuance
of that conversation, and draft the two user-owned planning files only when the
user asks for drafts.
Running /onboard never starts this skill. Empty plans never require it. A user
who writes detailed plans manually, has another AI conversation, or arrives with
finished plans continues directly to /overview exactly as before.
For a focused idea or technical tradeoff without drafting plans, use /explore.
Discovery develops the broader product plans.
Read only the planning and project facts needed for the conversation:
blueprint/project-plan.mdblueprint/build-plan.mdblueprint/context/project-overview.md only when the user is revisiting an
established project's directionClassify each planning file as a template, partial draft, or substantive plan. Never treat existing user content as disposable. When either plan has real content, summarize what it already establishes and ask whether the user wants to deepen it, revise a specific direction, or use it unchanged as conversation context. Do not replace it with a fresh generic plan.
Start with a short working hypothesis about the project and name the most important unknown. Then ask one focused question. Do not draft either plan yet.
Ask one meaningful question at a time and let each answer shape the next one. Prefer a likely interpretation the user can correct over a vague request for more detail. Explain a tradeoff when the answer would materially change scope, architecture, cost, or build order.
Cover the areas that matter to this project, not a fixed questionnaire:
Depth is the goal. Follow a consequential answer until its implications are clear instead of racing to the next category. Do not ask the user to repeat facts already established in the conversation or repository. Do not force irrelevant topics merely to complete a checklist.
Follow the proportional-engineering contract in AGENTS.md: ask about optional
usage or trust constraints only when they materially change the solution, record
established non-requirements, and leave unknowns blank.
Periodically return a compact discovery snapshot with:
The snapshot keeps a long conversation coherent. It is not permission to write the plans.
Do not end discovery because a preset number of questions has been reached. It is ready to draft when:
If the user asks for drafts while a material gap remains, name the gap and ask whether to continue discovery or preserve it as an explicit TODO. Respect the choice. The user may also stop at any time and write the plans manually.
When the user asks for drafts, produce complete proposed contents for both files without writing them yet.
For blueprint/project-plan.md:
For blueprint/build-plan.md:
/feature specs rather than turning the
roadmap into a task dumpIf substantive plans already exist, preserve their information and completed build-plan numbering. Clearly identify proposed additions, removals, or changed decisions.
End by asking the user to review the full drafts. Do not write either file in the same response that first presents them.
Write the approved drafts only after the user explicitly approves them. If the user requests changes, revise the drafts and show the affected sections again before writing.
After writing:
blueprint/context/project-overview.md/overview or $overview as the next optional command when the user
is satisfied with the plans/overview,
/feature, or any other Blueprint command./onboard, because planning files are
empty, or because a project is new.project-plan.md, while keeping
build-plan.md high-level and trackable.Follow blueprint/context/ai-interaction.md. During discovery, ask one focused
question per turn. For snapshots and draft reviews, use concise headings and
lists so confirmed decisions and remaining gaps are easy to inspect.
© aiblueprinthq, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file in .agents/skills/discovery of aiblueprinthq/ai-blueprint.
Open the folder on GitHubat commit 96222b7
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 |
|---|---|---|---|---|---|---|
| Discovery this skillaiblueprinthq/ai-blueprint | 463 | — | ~2.1k | Automated safety check: Pass | MIT | |
| CCPM Project Managementautomazeio/ccpm | 8.4k | — | ~1.1k | Automated safety check: Pass | MIT | |
| Uvastral-sh/claude-code-plugins | 313 | 2 repos | ~980 | Automated safety check: Pass | Apache-2.0 | |
| Project Managementkunchenguid/firstmate | 7.8k | — | ~2.1k | Automated safety check: Pass | MIT | |
| Hivemind Goalsactiveloopai/hivemind | 1.6k | — | ~1.7k | Automated safety check: Notes | Apache-2.0 | |
| Ichartjswanghetommy/ichartjs | 352 | — | ~4.3k | Automated safety check: Pass | Apache-2.0 |
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.
astral-sh/claude-code-plugins
Guide for using uv, the Python package and project manager. An agent skill from astral-sh/claude-code-plugins.
kunchenguid/firstmate
Agent-only procedure for Firstmate project management. An agent skill from kunchenguid/firstmate.
activeloopai/hivemind
Create, track and update team goals via the Deeplake virtual filesystem at memory/goal/.
wanghetommy/ichartjs
Plan, validate, render, explain, and safely edit iChart.js visualizations from tabular, project, or diagram data.
activeloopai/hivemind
Create, track and update team goals in Hivemind via the hivemind CLI.
aiblueprinthq/ai-blueprint
Adopt Blueprint into an existing brownfield codebase by surveying shipped behavior and generating plans, standards, commands, adapter choices, and visibility setup.
aiblueprinthq/ai-blueprint
Set up or normalize one project Verify command and matching GitHub Actions checks while preserving existing CI, with an optional local pre-push hook.
aiblueprinthq/ai-blueprint
Run a Blueprint health and context check covering setup, adapters, commands, visibility, plans, overview freshness, configuration, dashboard state, and workflow drift.
aiblueprinthq/ai-blueprint
Turn the next, named, or numbered build-plan feature into a buildable current-feature.md spec with small steps and done-when criteria.
aiblueprinthq/ai-blueprint
Onboard a fresh or early scaffold after Blueprint is overlaid by tuning commands, standards, adapters, visibility, and context loading.
aiblueprinthq/ai-blueprint
Validate and normalize project-plan.md and build-plan.md, then generate the durable project-overview.md used by agents.
Categories
Run an optional guided product-discovery interview and draft project-plan.md and build-plan.md only after the user is ready. Discovery is an agent skill from aiblueprinthq/ai-blueprint.md only after the user is ready.
Discovery fits situations like: guided planning; thinking through a new product; deepening plans.
Run `npx skills add aiblueprinthq/ai-blueprint --skill discovery -a claude-code`. Or copy the skill folder (.agents/skills/discovery in aiblueprinthq/ai-blueprint) into .claude/skills/discovery in your project. Claude Code loads it when a task matches its description.
Run `npx skills add aiblueprinthq/ai-blueprint --skill discovery -a codex`. Or copy the skill folder (.agents/skills/discovery in aiblueprinthq/ai-blueprint) into .agents/skills/discovery in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aiblueprinthq/ai-blueprint --skill 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/discovery, .gemini/skills/discovery, .github/skills/discovery and .opencode/skills/discovery in your project.
SKILL.md names no scripts, command-line tools or credentials: Discovery is instructions for the agent only.
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.
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.
Discovery is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.1k tokens (SKILL.md is roughly 8.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Discovery: CCPM Project Management (automazeio/ccpm, 8.4k stars), Uv (astral-sh/claude-code-plugins, 313 stars), Project Management (kunchenguid/firstmate, 7.8k stars) and Hivemind Goals (activeloopai/hivemind, 1.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
aiblueprinthq (a GitHub organization) maintains it in aiblueprinthq/ai-blueprint, which has 463 GitHub stars. The repository holds 20 skills in this directory. The repository was last updated on October 8, 2026.
Source: aiblueprinthq/ai-blueprint on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.