plan-feature

plan-feature is a skill for Claude Code from blockmatic/basilic. It costs 25 tokens per session (371 once invoked), scanned A, original, MIT.

A feature-planning workflow that turns a new idea into an organised implementation structure.

In plain words
What is it for?
Use it to prepare a feature from its initial plan through the structure needed to implement it.
Why use it?
It reduces the risk of starting development without clear steps, boundaries, or a workable structure.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter. Also seen: installed under .agents/ (shared by several agents).

Good fit Use it to prepare a feature from its initial plan through the structure needed to implement it.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/blockmatic/basilic/plan-feature
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.

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

Made for: Claude Code.

Wrote 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.

agentmods badge for plan-feature

README.md
[![agentmods](https://agentmods.dev/badge/skills/blockmatic/basilic/plan-feature.svg)](https://agentmods.dev/skills/blockmatic/basilic/plan-feature)
Your own site
<a href="https://agentmods.dev/skills/blockmatic/basilic/plan-feature"><img src="https://agentmods.dev/badge/skills/blockmatic/basilic/plan-feature.svg" alt="Measured on agentmods" height="20"></a>
Per session 25 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 371 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00025 $0.00371
Opus 5 $0.00013 $0.00186
Sonnet 5 $0.00005 $0.00074
Haiku 4.5 $0.00003 $0.00037

Measured 2d ago against content hash 8b5ed391fe59, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, 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.

.agents/skills/workflow/plan-feature/SKILL.md · 29 lines

What it actually says

Purpose and inputs

Use the requested outcome, existing plan or issue, relevant implementation, rules, and technical docs. Planning alone does not authorize implementation or Git changes.

Steps

  1. State goals, non-goals, acceptance criteria, and 3–5 material assumptions. Resolve consequential ambiguity; continue with reversible details already covered by the request.
  2. Inspect the affected packages, their README and scripts, and existing behavior. For durable decisions, load FIRST in the repository's prescribed order and use one primary station.
  3. Divide work into the smallest complete user-visible slices. For each, name likely files, dependencies, an observable acceptance condition, and the existing command or manual check that proves it.
  4. Put uncertain dependencies early. Include error paths, compatibility, generated sources, and recovery where relevant. Use a diagram only when relationships need one.
  5. Save to the existing plan location or the user's chosen destination. Include Goals, Assumptions, ordered tasks, Risks/Open Questions, and References (rules, skills, docs). Do not create another backlog or overwrite another task's unfinished plan.

Verification

  • Each slice has a result a reviewer can observe and a concrete verification method.
  • Dependencies and consequential unresolved decisions are explicit.
  • Commands come from inspected scripts; generated outputs have an owning source.
  • The plan is reviewable without reconstructing this conversation.

Handoff

Return the plan location, unresolved decisions, and first implementable slice. If the user also requested implementation, continue within that authorization; otherwise finish with the plan. Do not create a branch or scaffold code just to plan.

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 Changed · +10 lines · +1 tokens per session 8b5ed391fe59
  2. 3d ago Changed · +1 lines 347e7169c016
  3. 5d ago First seen · 18 lines · 24 tokens per session scan A 731756fa09f8

Subscribe to this mod's changes

plan-feature is a skill published in the GitHub repository blockmatic/basilic (89 stars, last pushed 2d ago), licensed MIT. It adds 25 tokens to every session and 371 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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