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 HoangNguyen0403/agent-skills-standard --skill plan-featuregit clone --depth 1 https://github.com/HoangNguyen0403/agent-skills-standardWrote 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/hoangnguyen0403/agent-skills-standard/plan-feature)<a href="https://agentmods.dev/skills/hoangnguyen0403/agent-skills-standard/plan-feature"><img src="https://agentmods.dev/badge/skills/hoangnguyen0403/agent-skills-standard/plan-feature/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/hoangnguyen0403/agent-skills-standard/plan-feature"><img src="https://agentmods.dev/badge/skills/hoangnguyen0403/agent-skills-standard/plan-feature.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00029 | $0.01129 |
| Opus 5 | $0.00015 | $0.00564 |
| Sonnet 5 | $0.00006 | $0.00226 |
| Haiku 4.5 | $0.00003 | $0.00113 |
Grade A, and why
plan-feature 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 9d 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Feature Skill
[!IMPORTANT] Plan a feature from BRD-lite brief or clear intent into PRD (What), decisions, implementation plan, and task slices.
Optional args: slug=, ticket=<id/url>, mode=interactive|autonomous|channel, channel=, auto_continue=true|false, profile=business|hybrid|technical.
Instructions
When the user asks to perform this workflow, execute the following steps:
Feature Planning Workflow (PRD / What)
Goal: Produce a PM-owned decision-complete PRD, delivery plan, and IT Department handoff before code starts.
Steps
- Load context:
- Load baseline PRD section and search
docs/brd/for the matching[slug]; if multiple candidates exist and intent is unclear, ask the user to choose/input the target slug. - Load BRD-lite, ticket text, existing specs, repo patterns,
common-product-requirements,common-operator-profile,quality-engineering-business-analysis, and matched framework skills. - Carry forward
operator_profile, BRD objective IDs, SMART metric, scope fence, assumptions, glossary, risks, and delivery context.
- Load baseline PRD section and search
- Interview:
- Draft a provisional PRD direction from current context before asking.
- Ask only for business logic, scope, constraints, and acceptance criteria that cannot be inferred.
- Ask max 3 blocking decisions at a time; include a recommended default and 2-3 options for each.
- Treat non-critical unknowns as explicit assumptions.
- Confirm problem statement, assumptions, target users, JTBD/use cases, platforms, data, analytics, security, performance, rollout, and non-goals.
- Confirm each requirement has owner, priority, and status.
- Confirm success metrics and guardrails that must not regress.
- Stop when requirements are actionable.
- Draft PRD:
- Save to
docs/prd/prd-[slug].mdwhen file writes are allowed. - Keep "what" separate from "how".
- Add stable requirement IDs and AC IDs.
- Use Given/When/Then AC when behavior can be misread.
- Check user stories for specific persona, business value, INVEST, happy path, edge path, and negative path.
- Link each requirement back to BRD-lite business objective.
- Include risk categories, rollout/ops, decision log, analytics/telemetry, and changelog.
- Mark unresolved blocking product decisions as blockers.
- Include a RACI table for BA, PM, architect, backend, frontend, mobile, QA, release, and business/UAT approver when more than one delivery role is involved.
- Save to
- Create implementation plan:
- Define components, contracts, data changes, migrations, risks, and verification.
- Slice work into fresh-context tasks.
- Map each task slice to requirement IDs, AC IDs, likely owner role, repo/module, expected artifact, and verification lane.
- Estimate each slice (t-shirt size + confidence); roll up a delivery-window range in time/cost terms for
operator_profile=business, points otherwise. - Identify whether
design-solutionis required before coding.
- Route:
- Continue when assumptions are non-critical; return BLOCKED for missing owner, untestable AC, approval, or release constraint.
- Architecture unclear ->
design-solution; approved build-ready plan with AC IDs and trace ->implementation-readiness.
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.
- 9d ago First seen · 99 lines · 29 tokens per session scan A dca7fcf31bd9
plan-feature is a skill published in the GitHub repository HoangNguyen0403/agent-skills-standard (565 stars, last pushed 3d ago), licensed MIT. It adds 29 tokens to every session and 1,129 once invoked, about $0.0001 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 2026-09-03.
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plan
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exec-plan
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