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.
git clone --depth 1 https://github.com/J-Pster/Psters_AI_WorkflowWrote 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/commands/j-pster/psters_ai_workflow/pwf-clarify)<a href="https://agentmods.dev/commands/j-pster/psters_ai_workflow/pwf-clarify"><img src="https://agentmods.dev/badge/commands/j-pster/psters_ai_workflow/pwf-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/commands/j-pster/psters_ai_workflow/pwf-clarify"><img src="https://agentmods.dev/badge/commands/j-pster/psters_ai_workflow/pwf-clarify.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00033 | $0.00772 |
| Opus 5 | $0.00016 | $0.00386 |
| Sonnet 5 | $0.00007 | $0.00154 |
| Haiku 4.5 | $0.00003 | $0.00077 |
Grade A, and why
pwf-clarify scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Clarify Requirements Before Planning/Execution
Use this command to reduce ambiguity before /pwf-plan finalization or before /pwf-work-plan execution.
Input
<clarify_input> #$ARGUMENTS </clarify_input>
If empty, ask: "Which plan should I clarify? (e.g. docs/plans/20260312-feature-plan.md)"
Step 1: Load context
- Identify target plan:
- If input is a
docs/plans/*.mdpath, use it directly. - Otherwise, find the most relevant recent plan by keywords.
- If input is a
- Read target plan fully.
- Read related docs when applicable:
docs/modules/<module>.mddocs/features/<feature>.mddocs/lambdas/<repo>.mddocs/solutions/patterns/critical-patterns.md(if exists)
Step 2: Ambiguity scan (taxonomy)
Scan and classify each category as Clear | Partial | Missing:
- Functional scope and success criteria
- Domain/data model and lifecycle transitions
- UX/interaction flows (empty/error/loading states)
- NFRs (security, performance, reliability, observability)
- Integration boundaries and failure modes
- Edge cases and conflict/concurrency handling
- Terminology consistency
- Completion signals (objective done criteria)
Step 3: Ask targeted questions
Ask up to 5 questions total, one at a time, prioritizing highest impact.
Question rules:
- Prefer multiple choice (2-5 options).
- Provide a recommended option and 1-2 line reasoning.
- Accept short custom answer when needed.
- Skip low-impact questions that do not change implementation.
Stop early when:
- Critical ambiguities are resolved, or
- user says "done"/"proceed", or
- question limit is reached.
Step 4: Write clarifications artifact
Write/update:
docs/plans/<plan-slug>.clarifications.md
Required structure:
# Clarifications — <Plan Title>
## Source Plan
- `docs/plans/<plan-file>.md`
## Session YYYY-MM-DD
- Q: ...
- Recommendation: ...
- Final Answer: ...
- Impact on Plan: ...
## Coverage Summary
| Category | Status | Notes |
|----------|--------|-------|
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.
- 10d ago First seen · 122 lines · 33 tokens per session scan A 8fdf117e3498
pwf-clarify is a command published in the GitHub repository J-Pster/Psters_AI_Workflow (289 stars, last pushed 5mo ago), licensed MIT. It adds 33 tokens to every session and 772 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.
Other commands, from other repositories
context
A project-context command that manages a .context directory containing decision notes, session logs, and history. It helps keep a record of why changes were made across Git branches and commits.
spec-research
A requirements-research command that turns a request into a set of constraints and checkable success criteria. It explores the relevant parts of a project in parallel and creates a structured proposal.
triage
Triage Linear issue with comprehensive analysis.
land
Cadence-tick autonomous PR babysitter (CI-fix, resolve, converge, merge, close, release).
sync
Manually trigger plan-sync to update downstream task specs after implementation drift.
slack-gif-creator
Toolkit for creating animated GIFs optimized for Slack, with validators for size constraints and composable animation primitives. This skill applies when users request animated GIFs or emoji animations for Slack from descriptions like "make me a GIF for Slack of X doing Y".