agentleFS
anombyte93anombyte93/prd-taskmaster/skills/discover/SKILL.md

discover

Skill608 starsChanged 9 months agoMITView on GitHub

Phase 1 of the prd-taskmaster pipeline: brainstorm-driven discovery. Delegates to superpowers:brainstorming in Interactive Mode (one adaptive question at a time), or self-brainstorms in Autonomous Mode when no user is present. Intercepts before the brainstorming chain hands off to writing-plans — this skill owns the exit. Extracts constraints, calibrates scale (Solo / Team / Enterprise), and advances the pipeline to GENERATE.

57 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use daily-arxiv, exp-eval and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • LambenthanSkill

    daily-arxiv

    每日从 arXiv 拉取新论文,过滤相关性,auto-ingest 高优先级论文,检测 SOTA 更新

    Also in 5 projects that use this

  • LambenthanSkill

    exp-eval

    实验判决门:Review LLM 独立评判实验结果 → 4 种判决路径 → 自动更新 claims confidence、ideas status、graph edges

    Also in 5 projects that use this

  • skyllwtSkill

    exp-pilot-eval

    Pilot result evaluation — read pilot results, apply success criteria, update idea page (pilot_result, failure_reason if failed), generate PILOT_VERDICT_REPORT. Called by /ideate Phase 5 after /exp-pilot-run.

    Also in 4 projects that use this

  • skyllwtSkill

    exp-pilot-run

    Pilot experiment execution — read Pilot Spec YAML, write pilot code, run experiment(Confirm with the user before operation and require the applicant to conduct manual inspection), return results. Called by /ideate Phase 5. Does NOT modify wiki pages or judge pass/fail.

    Also in 4 projects that use this

  • phanghonghaoSkill

    poster

    HTML/CSS A4 海报生成。从沙龙/活动 Markdown 文件生成科技风 A4 海报 PDF/PNG。Use when user mentions: poster, 海报, 海报生成, make poster, generate poster, 活动海报, 沙龙海报.

    Also in 4 projects that use this

  • +6 more from Lambenthan
  • +1 more from skyllwt

The file

Show its rules and text

We split this skill into the rules it gives an agent

16 rules. 0 are common, 9 are distinctive, and 7 are very specific to this project.

  • 0

    Common

    Most of the 50 edited versions we read keep these.

  • 9

    Distinctive

    This author's own choices. Worth a look.

  • 7

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Keep the Interactive versus explicitly authorised Autonomous distinction.

    line 38
  2. Very specific:

    Call mcp__plugin_prd_go__check_gate(phase="DISCOVER", evidence={}) for diagnostics.

    line 43
  3. Distinctive:

    Re-entry: if the gate reports violations, report them and stop — it protects against re-running a completed phase or skipping ahead from …

    line 52
  4. Very specific:

    INTERCEPT POINT: when brainstorming signals readiness to chain to writing-plans, STOP.

    line 83
  5. Very specific:

    Read the goal statement from skill args or session-context/CLAUDE-soul-purpose.md.

    line 97
  6. Very specific:

    Read session-context/CLAUDE-activeContext.md for project context.

    line 99
  7. Very specific:

    Write discovery notes directly to session-context/discovery-{timestamp}.md answering every question the interactive flow would ask:

    line 100
  8. Distinctive:

    Commit the discovery file.

    line 112
  9. Very specific:

    After brainstorming completes, present via AskUserQuestion:

    line 123
  10. Distinctive:

    If user says "refine" → ask what to change, update the summary, re-present.

    line 137
  11. Distinctive:

    If user approves → capture as the discovery output and proceed to exit gate.

    line 138
  12. Very specific:

    Write the discovery summary to session-context/discovery-{timestamp}.md and commit it.

    line 142
  13. Distinctive:

    If brainstorming (or self-brainstorming) produces thin answers, fill gaps with reasonable assumptions instead of forcing extra questions:

    line 148
  14. Distinctive:

    Document every assumption in the discovery summary so GENERATE can surface them in the spec.

    line 156
  15. Distinctive:

    Before moving to GENERATE, explicitly extract and list all constraints mentioned during discovery.

    line 161
  16. Distinctive:

    After approval (Interactive) or commit (Autonomous), constraints captured, and scale classified:

    line 196

“Common” is measured: kept by at least 6 in 10 of the 50 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Phase 1: Discover

Declarative phase skill. Invoked by the prd-taskmaster orchestrator when current_phase is DISCOVER. Never called directly by a user.

The one rule: invoke superpowers:brainstorming for discovery, intercept before it chains to writing-plans — we control the exit, not the brainstorm skill.

Task provider routing comes first

For atlas-kanban, perform the discovery, approval, constraint extraction and scope calibration below, but do not call the file-mode check_gate/advance_phase operations. Return the approved summary and constraints to the provider-aware orchestrator for phases/GENERATE.md; no task store is created during discovery. Keep the Interactive versus explicitly authorised Autonomous distinction. The file-mode pipeline transitions below apply only to taskmaster-file.

Entry gate

  1. Call mcp__plugin_prd_go__check_gate(phase="DISCOVER", evidence={}) for diagnostics.

    check_gate is an EXIT gate: it verifies the evidence to advance, not to enter. On first DISCOVER entry you have no evidence yet (the User Approval / Self-Approval Gate below produces user_approved=true OR auto_classification=CLEAR with assumptions_documented), so a gate_passed: false here is EXPECTED — the state machine's legal transitions already guarantee only legal entry.

    • First entry (no evidence yet): note the result and continue with the Procedure.
    • Re-entry: if the gate reports violations, report them and stop — it protects against re-running a completed phase or skipping ahead from SETUP.
  2. Detect execution context. If any of the following signals are present, switch to Autonomous Mode:
    • .claude/ralph-loop.local.md exists in the project root
    • An auto-enter / auto-approve daemon is running against this session
    • The skill was invoked with an explicit --autonomous flag
    • Parent orchestrator is a cron, /pentest-wtf, or /ralph-loop Otherwise proceed in Interactive Mode (default).

Discovery checklist

Copy into your response before running the procedure:

DISCOVERY CHECKLIST:
- [ ] Mode detected (Interactive vs Autonomous)
- [ ] Goal captured from skill args or soul purpose
- [ ] Adaptive questions completed (one at a time)
- [ ] Constraints extracted and listed
- [ ] Scale classified (Solo / Team / Enterprise)
- [ ] Discovery summary captured for GENERATE phase
- [ ] User approved (Interactive) or summary committed (Autonomous)

Interactive Mode (default — user present)

  1. Take the user's goal / description from the skill invocation args.
  2. Invoke superpowers:brainstorming with the goal as input.
  3. Brainstorming runs its adaptive question flow — one domain-agnostic question at a time. Let it drive the Q&A rhythm.
  4. INTERCEPT POINT: when brainstorming signals readiness to chain to writing-plans, STOP. Do NOT let it invoke writing-plans. Capture the brainstorm output (design, requirements, decisions) into local state instead. The prd-taskmaster orchestrator owns the handoff — not superpowers:brainstorming.
  5. Present the summary to the user for approval via AskUserQuestion (see User Approval Gate below).

Autonomous Mode (no user present)

Do NOT invoke superpowers:brainstorming — it blocks on user input and will stall an unattended session. Instead, self-brainstorm using this template:

  1. Read the goal statement from skill args or session-context/CLAUDE-soul-purpose.md.
  2. Read session-context/CLAUDE-activeContext.md for project context.
  3. Write discovery notes directly to session-context/discovery-{timestamp}.md answering every question the interactive flow would ask:
    • Who is this for?
    • What problem does it solve?
    • What are the success metrics?
    • What are the constraints (tech stack, timeline, team, budget, integrations, regulatory)?
    • What's explicitly out of scope?
    • What's the scale (Solo / Team / Enterprise)?
  4. Self-approve: the skill acts as both interrogator and approver. Document assumptions explicitly so the user can audit them on wake-up.
  5. Commit the discovery file. The git history becomes the audit trail — if the user later disagrees, they can reset to that commit and re-run.

Autonomous mode is first-class, not degraded. A well-run autonomous discovery produces a spec the user reads on wake-up and says "yes, that's what I meant" without edits. If you find yourself needing to ask more than two questions the user didn't anticipate, the discovery is under-specified — stop and write a handoff note instead of proceeding.

User Approval Gate (Interactive Mode)

After brainstorming completes, present via AskUserQuestion:

Discovery Complete:
  Goal: [one sentence]
  Audience: [who it's for]
  Approach: [proposed solution]
  Key decisions: [list]
  Constraints: [known limitations]
  Scale: [Solo | Team | Enterprise]

Proceed to generate spec? (or refine further)
  • If user says "refine" → ask what to change, update the summary, re-present.
  • If user approves → capture as the discovery output and proceed to exit gate.

Self-Approval Gate (Autonomous Mode)

Write the discovery summary to session-context/discovery-{timestamp}.md and commit it. No interactive approval is required, but assumptions MUST be explicit in the written summary so the user can audit on wake-up.

Smart Defaults

If brainstorming (or self-brainstorming) produces thin answers, fill gaps with reasonable assumptions instead of forcing extra questions:

  • Target audience: small team (< 10 users) unless specified otherwise.
  • Timeline: MVP in 4–6 weeks.
  • Tech stack: inferred from requirements — do not pick arbitrarily.
  • Scale: moderate (hundreds of users, not millions).

Document every assumption in the discovery summary so GENERATE can surface them in the spec.

Constraint Extraction (MANDATORY before advancing)

Before moving to GENERATE, explicitly extract and list all constraints mentioned during discovery. Emit this block:

CONSTRAINTS CAPTURED:
- Tech stack: [e.g., "must use Python", "React frontend", "no new dependencies"]
- Timeline: [e.g., "MVP in 2 weeks", "no deadline"]
- Team: [e.g., "solo developer", "3-person team"]
- Budget: [e.g., "free tier only", "$500/month max"]
- Integration: [e.g., "must work with existing Postgres DB", "connects to Stripe"]
- Regulatory: [e.g., "HIPAA compliant", "GDPR", "none specified"]
- Domain-specific: [e.g., "authorized pentest scope: 10.0.0.0/24 only",
  "learning goal: intermediate level"]

Present this list alongside the discovery summary. These constraints MUST be passed to GENERATE — they inform spec content, task decomposition depth, and acceptance criteria. If a constraint is mentioned in discovery but missing from the spec, that's a bug.

Scope Calibration

Infer project scale from discovery answers and set decomposition guidance:

ScaleSignalTask CapSubtask Depth
Solo"just me", "side project", "learning"8–12 tasks2–3 subtasks each
Team"small team", "MVP", "product", "startup"12–20 tasks3–5 subtasks each
Enterprise"compliance", "multiple teams", "platform"20–30 tasks5–8 subtasks each

Pass the scale classification to GENERATE so task count is calibrated, not arbitrary.

Exit gate

After approval (Interactive) or commit (Autonomous), constraints captured, and scale classified:

  1. Call mcp__plugin_prd_go__advance_phase(expected_current="DISCOVER", target="GENERATE", evidence={"user_approved": True, "constraints_captured": True, "scale": "<Solo|Team|Enterprise>", "assumptions_documented": True}). The call atomically transitions pipeline.json from DISCOVER to GENERATE. The expected_current field is the compare-and-swap guard; evidence is stored under phase_evidence[GENERATE] for audit.
  2. Return control to the orchestrator (prd-taskmaster skill). Do NOT invoke GENERATE directly — the orchestrator re-reads current_phase and routes.

Red flags (stop and report, do not paper over)

  • "Brainstorming wants to call writing-plans — I'll let it" → NO. Intercept. The prd-taskmaster pipeline owns the exit, not superpowers:brainstorming.
  • "User hasn't answered, I'll pick for them in Interactive Mode" → NO. If stalled, ask one more targeted question or write a handoff note — don't silently self-approve in Interactive Mode.
  • "Autonomous mode — I'll invoke superpowers:brainstorming anyway" → NO. It blocks on user input and will stall the session. Self-brainstorm with the template above.
  • "Constraints are obvious, I'll skip the CONSTRAINTS CAPTURED block" → NO. GENERATE reads this block — missing constraints become missing spec sections downstream.
  • "I can call advance_phase without check_gate" → NO. Gate first, always.

Non-exits

This skill does not use explicit process termination. A hard block reports the reason and returns control to the orchestrator; the orchestrator decides whether to surface to the user.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.