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 skills add tikalk/adlc-team-skills --skill product-clarifygit clone --depth 1 https://github.com/tikalk/adlc-team-skillsWrote 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/tikalk/adlc-team-skills/product-clarify)<a href="https://agentmods.dev/skills/tikalk/adlc-team-skills/product-clarify"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/product-clarify/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tikalk/adlc-team-skills/product-clarify"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/product-clarify.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Memory Poisoning · line 62 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
- high Memory Poisoning · line 94 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
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 5.1 | $0.00041 | $0.02045 |
| Opus 5 | $0.00020 | $0.01022 |
| Sonnet 5 | $0.00008 | $0.00409 |
| Haiku 4.5 | $0.00004 | $0.00204 |
Grade A, and why
product-clarify 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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 266 lines — stays where its author put it; the contents beside it link to each section on GitHub.
product-clarify
What this skill does
Reviews existing PDRs for quality gaps, asks targeted clarification questions, and promotes approved PDRs to Accepted status. This is the quality gate before PRD generation.
Input: Individual PDR-*.md files in .adlc/drafts/pdr/ (status Proposed or Discovered)
Output: Updated PDR-*.md files (status Accepted where approved), regenerated pdr.md index
When to use
- After
/product-specifyor/product-initto refine initial PDRs - Before
/product-implementto approve PDRs (required — implement skips non-Accepted) - Periodic PDR review before milestones
- Resolving inconsistency flags from cross-feature-area analysis
When NOT to use
- No PDRs exist (use
/product-specifyor/product-initfirst)
Execution Steps
Phase 1: Load PDRs
- Run setup script:
sh: scripts/bash/setup-product-clarify.sh [--json]
ps: scripts/powershell/setup-product-clarify.ps1
- Read all PDR files from
{REPO_ROOT}/.adlc/drafts/pdr/PDR-*.md - Read constitution from
{REPO_ROOT}/.adlc/memory/constitution.mdif exists - Build inventory:
| PDR | Title | Status | Category |
|-----|-------|--------|----------|
| PDR-001 | Target Market | Proposed | Problem |
| PDR-002 | Primary Persona | Proposed | Persona |
Phase 2: PDR Quality Analysis
Check each PDR against standards:
| Dimension | Check | Severity if Missing |
|---|---|---|
| Context | Problem clearly stated | MEDIUM |
| Decision | Actionable, testable | HIGH |
| Consequences | Positive AND negative | HIGH |
| Success Metrics | Defined with targets | HIGH |
| Alternatives | At least 2 with neutral trade-offs | HIGH |
| Constitution | Aligns with vision | CRITICAL |
Quality checklist:
- Clear context explaining the problem/opportunity
- Explicit, actionable decision statement
- Positive AND negative consequences documented
- At least 2 alternatives with neutral trade-offs (not "rejected because")
- Success metrics defined
- Risks identified with mitigation strategies
- Valid status value
- No conflicts with other PDRs
- Alignment with constitution/vision principles
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago Changed 3b0629050332
- 11d ago First seen · 266 lines · 41 tokens per session scan A c5c3d5c47e78
product-clarify is a skill published in the GitHub repository tikalk/adlc-team-skills (133 stars, last pushed today), licensed MIT. It adds 41 tokens to every session and 2,045 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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issue-creation
Trigger: issue creation, bug reports, feature requests, or issue approval. Create and triage GitHub issues from repository evidence.
sdd-tasks
Break an SDD change into implementation tasks. Trigger: orchestrator launches task planning for a change.
systemic-issue-triage
Trigger: new issue, bug report, triage, backlog, issue flood, community report, root cause, dead-end, blocked user. Attack issues by root class, never one-by-one; fixes must shrink the system, not grow it.
workspace
Dynamic multi-repo and monorepo awareness for Claude Code. Analyze workspace topology, track API contracts, and maintain cross-repo context.
ticket-craft
Create Jira/Asana/Linear tickets optimized for Claude Code execution - AI-native ticket writing.
team-coordination
Multi-person projects - shared state, todo claiming, handoffs.