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/knitli/codeweaver/specifygit clone --depth 1 https://github.com/knitli/codeweaverWhat 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 | $0.00000 | $0.00339 |
| Opus 5 | $0.00000 | $0.00169 |
| Sonnet 5 | $0.00000 | $0.00068 |
| Haiku 4.5 | $0.00000 | $0.00034 |
Grade A, and why
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 yesterday.
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
92% identical to specify — 7 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.
What it actually says
description: Create or update the feature specification from a natural language feature description.
The user input to you can be provided directly by the agent or as a command argument - you MUST consider it before proceeding with the prompt (if not empty).
User input:
$ARGUMENTS
The text the user typed after /specify in the triggering message is the feature description. Assume you always have it available in this conversation even if $ARGUMENTS appears literally below. Do not ask the user to repeat it unless they provided an empty command.
Given that feature description, do this:
- Run the script
.specify/scripts/bash/create-new-feature.sh --json "$ARGUMENTS"from repo root and parse its JSON output for BRANCH_NAME and SPEC_FILE. All file paths must be absolute. IMPORTANT You must only ever run this script once. The JSON is provided in the terminal as output - always refer to it to get the actual content you're looking for. - Load
.specify/templates/spec-template.mdto understand required sections. - Write the specification to SPEC_FILE using the template structure, replacing placeholders with concrete details derived from the feature description (arguments) while preserving section order and headings.
- Report completion with branch name, spec file path, and readiness for the next phase.
Note: The script creates and checks out the new branch and initializes the spec file before writing.
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.
- yesterday First seen · 29 lines · 0 tokens per session scan A b068880950e6
specify is a command published in the GitHub repository knitli/codeweaver (12 stars, last pushed 2mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 339 tokens. A static security scan graded it A with 0 findings. It is 92% identical to specify, differing in 7 lines, and is treated as a copy.
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