Borrowing it
Nothing to install: this file belongs to shep-ai/shep. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/shep-ai/shep/main/.claude/skills/shep-kit-plan/SKILL.mdgit clone --depth 1 https://github.com/shep-ai/shepWrote 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/shep-ai/shep/shep-kit-plan)<a href="https://agentmods.dev/skills/shep-ai/shep/shep-kit-plan"><img src="https://agentmods.dev/badge/skills/shep-ai/shep/shep-kit-plan/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/shep-ai/shep/shep-kit-plan"><img src="https://agentmods.dev/badge/skills/shep-ai/shep/shep-kit-plan.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 | $0.00066 | $0.01768 |
| Opus 5.5 | $0.00026 | $0.00707 |
| Sonnet 5.5 | $0.00013 | $0.00354 |
| Haiku 4.5 | $0.00007 | $0.00177 |
Grade A, and why
shep-kit:plan 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 1mo 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 — 220 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create Implementation Plan
Generate a detailed implementation plan with architecture overview and task breakdown.
Full workflow guide: docs/development/spec-driven-workflow.md
Prerequisites
- Feature spec exists at
specs/NNN-feature-name/spec.yaml - Research completed at
specs/NNN-feature-name/research.yaml - On the feature branch
feat/NNN-feature-name
GATE CHECK (Mandatory)
Before starting planning, verify:
- Read
research.yamland check theopenQuestionsfield - If any items have
resolved: false: STOP and inform user:Cannot proceed with planning. Open questions in research.yaml must be resolved first. Please complete research or mark questions as resolved.
- Only proceed when all open questions have
resolved: trueor theopenQuestionsarray is empty
Workflow
1. Review Spec & Research
Read both YAML source files to understand:
- Requirements and success criteria (
spec.yaml) - Technical decisions and constraints (
research.yaml) - Affected areas and dependencies
2. Design Architecture
Create high-level architecture:
- Component diagram (ASCII or Mermaid)
- Data flow between components
- Integration points with existing code
3. Define Implementation Phases (MANDATORY TDD STRUCTURE)
CRITICAL: Plans MUST follow Test-Driven Development (TDD) with RED-GREEN-REFACTOR cycles.
Break implementation into phases following TDD:
- Foundational phases (no tests): Build pipeline, TypeSpec models, configuration
- TDD Cycle phases: For each layer (Domain, Application, Infrastructure):
- RED: Write failing tests first
- GREEN: Write minimal code to pass tests
- REFACTOR: Clean up while keeping tests green
- Each phase should be independently testable
- Order by dependencies (foundational first)
- Identify parallelizable work
4. Identify Files to Create/Modify
For each phase, list:
- New files: Path and purpose
- Modified files: Path and changes needed
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.
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.
- 1mo ago First seen · 220 lines · 66 tokens per session scan A 225865429bc0
shep-kit:plan is a skill published in the GitHub repository shep-ai/shep (267 stars, last pushed yesterday), licensed MIT. It adds 66 tokens to every session and 1,768 once invoked, about $0.0003 per session on Opus 5.5. 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.
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