plan-feature

A planning tool that turns a backlog item into smaller work slices, a Gherkin acceptance specification, and an ordered implementation plan. Gherkin is a plain-text format for describing observable software behavior.

In plain words
What is it for?
Use it to plan a feature from backlog and requirements files, resolve blocking questions, or review and revise an existing feature plan.
Why use it?
It exposes missing requirements and dependencies before coding begins, so the team can agree on what the feature must do and how it will be checked.

Skill for Claude CodeCodex

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/leifericf/agentic-sdk/plan-feature
Any agent
npx skills add leifericf/agentic-sdk --skill plan-feature
Clone the repo
git clone --depth 1 https://github.com/leifericf/agentic-sdk

Made for: Claude Code, Codex.

Per session 19 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,005 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.

ModelPer sessionOnce invoked
Fable 5 $0.00019 $0.01005
Opus 5 $0.00010 $0.00502
Sonnet 5 $0.00004 $0.00201
Haiku 4.5 $0.00002 $0.00101

Measured 2d ago against content hash d825250ec513, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 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-feature/SKILL.md · 79 lines

How it starts

The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.

plan-feature

Turn a selected backlog item into a dependency-ordered plan with a Gherkin acceptance gate and parallel quality-dimension assessments. Two modes: plan (default) and review (revise an existing plan).

Procedure

  1. Read product-backlog.md, product-requirements.md, decision-log.md, and open-questions.md. In review mode, read the existing ~/.agentic-sdk/<project>/artifacts/planning/tasks/plan-<slug>.md instead and treat its Functional Snapshot and Gherkin as source of truth. Surface and resolve any [Blocking] item affecting this feature first.
  2. Functional elicitation gate. Read the backlog item and relevant requirements; fold in resolved open-question answers. If requirements are missing or ambiguous, ask in this order, at most two batches of three questions: problem and intent; success criteria (observable); user outcomes (must do, must never happen, edge cases); user flow (primary, alternate, friction); business and domain rules; integrations and their failure behavior; prioritization (MVI, what is deferred); constraints (privacy, security, compliance, operational); delight and quality bar. Do not proceed until you can answer in plain language: the primary user and goal, observable success, the primary flow, what must never happen, the key edge cases, the business rules, the integrations and their failure behavior, the MVI, and what is deferred. If any blocker remains, add a [Blocking] open question and return blocked.
  3. Write the Gherkin specification. Treat it as source of truth for feature-level acceptance: business language and user-observable outcomes, not UI mechanics. Three to seven scenarios for the MVI, deterministic, each asserting externally visible state. Include at least one happy path, one must-never-happen, one key edge case, and one integration or dependency-failure scenario where applicable. Use Feature: with a short narrative, Background: only for truly shared preconditions, Rule: to group business rules, and Scenario Outline: with Examples: for permutations.
  4. Fan out the four planning dimensions: dispatch assess-observability, assess-testing, assess-data, and assess-rollout in parallel (module-batch fan-out; if your context has no sub-agent tool, run them inline per orchestration.md). Collect each one-line EDN assessment.
  5. Plan chunks and tasks. Decompose into two to six independently testable chunks that each deliver user value and reduce risk; plan the next chunk in full and keep later chunks lighter. Write tasks commit-per-task, each leaf completable in one commit. Capture unrelated later ideas under Inbox (untriaged) in product-backlog.md; do not expand scope unless the user changes the definition of done. Keep the plan a forward-only DAG: security and verification ride with each chunk, not bolted on at the end.
  6. Write the plan to ~/.agentic-sdk/<project>/artifacts/planning/tasks/plan-<feature_slug>.md, filling the section skeleton in plan-template.md. Fold the four dimension assessments into their sections (Observability, Testing Strategy, Data and Migrations, Rollout and Verify); surface any N/A with its reason. Follow the project descriptor's VCS and commit form, not any retired commit mechanics in the skeleton.
  7. Review mode. Over an existing plan, surface the gaps that cause rework: success criteria that are not observable, flow ambiguity, missing must-never-happen outcomes, unstated edge cases, ambiguous rules, unspecified integration failure behavior, and an unclear split between the MVI and the deferred scope. Ask the smallest set of clarifying questions, at most two batches of three, in the elicitation order above; prefer plain language and choice questions. Revise the Functional Snapshot, Gherkin, chunks, and tasks, and write the plan back.

Read the full file on GitHub · 79 lines

Files

What ships with it

1 file 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.

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.

  1. 2d ago First seen · 79 lines · 19 tokens per session scan A d825250ec513

Subscribe to this mod's changes

plan-feature is a skill published in the GitHub repository leifericf/agentic-sdk (5 stars, last pushed 13d ago), licensed MIT. It adds 19 tokens to every session and 1,005 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 2026-08-31.

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