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.
npx agentmods add commands/spillwavesolutions/agent-brain/speckit.specifygit clone --depth 1 https://github.com/SpillwaveSolutions/agent-brainWhat 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 | $0.00013 | $0.02834 |
| Opus 5 | $0.00006 | $0.01417 |
| Sonnet 5 | $0.00003 | $0.00567 |
| Haiku 4.5 | $0.00001 | $0.00283 |
Grade A, and why
speckit.specify 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.
This is a copy
73% identical to specify — 195 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 261 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spec directory: All SDD artifacts live under
.speckit/(features, templates, scripts, memory).
User Input
$ARGUMENTS
You MUST consider the user input before proceeding (if not empty).
Outline
The text the user typed after /speckit.specify in the triggering message is the feature description. Assume you always have it available in this conversation even if $ARGUMENTS appears literally below. Do not ask the user to repeat it unless they provided an empty command.
Given that feature description, do this:
-
Generate a concise short name (2-4 words) for the branch:
- Analyze the feature description and extract the most meaningful keywords
- Create a 2-4 word short name that captures the essence of the feature
- Use action-noun format when possible (e.g., "add-user-auth", "fix-payment-bug")
- Preserve technical terms and acronyms (OAuth2, API, JWT, etc.)
- Keep it concise but descriptive enough to understand the feature at a glance
- Examples:
- "I want to add user authentication" → "user-auth"
- "Implement OAuth2 integration for the API" → "oauth2-api-integration"
- "Create a dashboard for analytics" → "analytics-dashboard"
- "Fix payment processing timeout bug" → "fix-payment-timeout"
-
Check for existing branches before creating new one:
a. First, fetch all remote branches to ensure we have the latest information:
git fetch --all --pruneb. Find the highest feature number across all sources for the short-name:
- Remote branches:
git ls-remote --heads origin | grep -E 'refs/heads/[0-9]+-<short-name>$' - Local branches:
git branch | grep -E '^[* ]*[0-9]+-<short-name>$' - Specs directories: Check for directories matching
.speckit/features/[0-9]+-<short-name>
c. Determine the next available number:
- Extract all numbers from all three sources
- Find the highest number N
- Use N+1 for the new branch number
- Remote branches:
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 · 261 lines · 13 tokens per session scan A 42a4389ca06d
speckit.specify is a command published in the GitHub repository SpillwaveSolutions/agent-brain (117 stars, last pushed 3d ago), licensed MIT. It adds 13 tokens to every session and 2,834 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 73% identical to specify, differing in 195 lines, and is treated as a copy.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
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.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
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.