A planning tool that breaks an approved product requirements document, or PRD, into implementation phases. Each phase records its difficulty, working process, covered requirements, and dependencies.

Use it to create a plan for forge-master, incorporate an optional technical specification, review past lessons, and prepare the phases for human approval.

It turns a feature description into an execution contract and checks that every acceptance criterion is covered without circular dependencies.

plan-design — Skill by alanvaa06

Install

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.

agentmods

npx agentmods add skills/alanvaa06/forge-master/plan-design

Any agent

npx skills add alanvaa06/forge-master --skill plan-design

Clone the repo

git clone --depth 1 https://github.com/alanvaa06/forge-master

Made for: Claude Code, Codex.

Per session 109 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,581 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00109	$0.02581
Opus 5	$0.00055	$0.01290
Sonnet 5	$0.00022	$0.00516
Haiku 4.5	$0.00011	$0.00258

Measured 2d ago against content hash 3d2f525a1519, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

plan-design 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 2d 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.

skills/plan-design/SKILL.md · 107 lines

How it starts

The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.

plan-design — PRD to Execution Contract (Human Gate 2)

Produce docs/forge/plans/plan-NNN.md from docs/forge/prd/NNN-name.md. After approval this file is the FROZEN execution contract — run asks nothing.

Step 1 — Load inputs

Read the target PRD docs/forge/prd/NNN-name.md (ask which N if ambiguous).
If docs/forge/specs/spec-NNN.md exists (produced by spec-design), read it. Phases then follow its File Map and Interfaces, notes: cite the spec sections a phase implements, and the spec's Risks inform tagging — a phase touching a listed risk does not start junior/light.
If NO spec exists and the PRD looks architecturally non-trivial (new interfaces, data models, multiple components that must agree), ASK the user ONCE before decomposing, as a lettered list (mark one Recommended with a concrete why) — never assume either way:

No spec found, and this PRD looks architecturally non-trivial. Next: a) Run /forge-master:spec-design first — Recommended, new interfaces / data models / components that must agree b) Plan directly — you accept resolving design inline as phases are decomposed

The user picks by replying with a letter. On (a), INVOKE forge-master:spec-design yourself via the Skill tool rather than asking the user to type it. For a clearly small task, proceed without asking — the spec is optional and subordinate to this plan.
Read docs/context/lessons.md. Past escalation lessons ("P-type X tagged light escalated — tag heavy when ") MUST inform your tagging. This is the triage learning loop.
Read templates/plan-template.md (from this plugin) as the output skeleton.

Step 2 — Decompose into phases

Group the PRD's ACs into phases (P1, P2, ...). Each phase is an independently committable, independently verifiable unit of work.
For each phase set:
- covers: the AC IDs it satisfies.
- depends_on: prerequisite P-ids. The graph MUST be acyclic. It defines what remains executable if a phase blocks.
- tier: junior (cheap-model subagent, low effort) or senior (top model, high effort). Start optimistic — junior unless evidence (PRD constraints, a relevant lesson) demands senior.
- process: light (inline implement -> write/run AC tests -> commit; no separate spec or review) or heavy (brief phase spec -> TDD red-green -> independent-subagent code review -> commit). Start light unless complexity/risk warrants heavy.
- success: covered ACs green + full repo test suite still passes.
- notes: risks, probable files, the reason for the tier/process choice (cite a lesson if one applied).

Read the full file on GitHub · 107 lines

Changes

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.

2d ago First seen · 107 lines · 109 tokens per session scan A 3d2f525a1519

Subscribe to this mod's changes

plan-design is a skill published in the GitHub repository alanvaa06/forge-master (1 stars, last pushed 1mo ago), licensed MIT. It adds 109 tokens to every session and 2,581 once invoked, about $0.0005 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 2026-08-31.

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