Borrowing it
Nothing to install: this file belongs to ddddjaak/se-skills. 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/ddddjaak/se-skills/main/.claude/commands/se-spec.mdgit clone --depth 1 https://github.com/ddddjaak/se-skillsWrote 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/commands/ddddjaak/se-skills/se-spec)<a href="https://agentmods.dev/commands/ddddjaak/se-skills/se-spec"><img src="https://agentmods.dev/badge/commands/ddddjaak/se-skills/se-spec.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00036 | $0.00240 |
| Opus 5 | $0.00018 | $0.00120 |
| Sonnet 5 | $0.00007 | $0.00048 |
| Haiku 4.5 | $0.00004 | $0.00024 |
Grade A, and why
se-spec 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 7d 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.
What it actually says
Invoke the se-skills:spec-authoring skill.
Prerequisites: architecture design and system requirements must exist. If missing, invoke se-skills:architecture-design and/or se-skills:requirements-decompose first.
Work through the five-step process:
- SELECT — confirm which specification(s) to generate: Software Outline Design, HW-SW Interface Spec, Test Plan, or all three
- GATHER — collect and version-verify all input artifacts; surface misaligned versions
- GENERATE — author specification content following defined templates. Every claim must trace to a requirement ID or architecture interface ID. Enforce: numbers not adjectives, empty sections are errors, TBDs must have owners and due dates
- CROSS-CHECK — verify internal consistency: all requirement references resolve, all interface definitions match architecture, no orphan content
- FINALIZE — present for human review and sign-off
Save outputs to docs/spec/[project]-[spec-type].md after user confirmation.
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.
- 7d ago First seen · 17 lines · 36 tokens per session scan A 98de718af2a4
se-spec is a command published in the GitHub repository ddddjaak/se-skills (4 stars, last pushed 1mo ago), licensed MIT. It adds 36 tokens to every session and 240 once invoked, about $0.0002 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.