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/plangit 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 | $0.00555 |
| Opus 5 | $0.00000 | $0.00278 |
| Sonnet 5 | $0.00000 | $0.00111 |
| Haiku 4.5 | $0.00000 | $0.00056 |
Grade A, and why
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 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
88% identical to plan — 9 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: Execute the implementation planning workflow using the plan template to generate design artifacts.
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
Given the implementation details provided as an argument, do this:
-
Run
.specify/scripts/bash/setup-plan.sh --jsonfrom the repo root and parse JSON for FEATURE_SPEC, IMPL_PLAN, SPECS_DIR, BRANCH. All future file paths must be absolute.- BEFORE proceeding, inspect FEATURE_SPEC for a
## Clarificationssection with at least oneSessionsubheading. If missing or clearly ambiguous areas remain (vague adjectives, unresolved critical choices), PAUSE and instruct the user to run/clarifyfirst to reduce rework. Only continue if: (a) Clarifications exist OR (b) an explicit user override is provided (e.g., "proceed without clarification"). Do not attempt to fabricate clarifications yourself.
- BEFORE proceeding, inspect FEATURE_SPEC for a
-
Read and analyze the feature specification to understand:
- The feature requirements and user stories
- Functional and non-functional requirements
- Success criteria and acceptance criteria
- Any technical constraints or dependencies mentioned
-
Read the constitution at
.specify/memory/constitution.md(path relative to repo root) to understand constitutional requirements. -
Execute the implementation plan template:
- Load
.specify/templates/plan-template.md(already copied to IMPL_PLAN path) - Set Input path to FEATURE_SPEC
- Run the Execution Flow (main) function steps 1-9
- The template is self-contained and executable
- Follow error handling and gate checks as specified
- Let the template guide artifact generation in $SPECS_DIR:
- Phase 0 generates research.md
- Phase 1 generates data-model.md, contracts/, quickstart.md
- Phase 2 generates tasks.md
- Incorporate user-provided details from arguments into Technical Context: $ARGUMENTS
- Update Progress Tracking as you complete each phase
- Load
-
Verify execution completed:
- Check Progress Tracking shows all phases complete
- Ensure all required artifacts were generated
- Confirm no ERROR states in execution
-
Report results with branch name, file paths, and generated artifacts.
Use absolute paths with the repository root for all file operations to avoid path issues.
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 · 51 lines · 0 tokens per session scan A 14dcb02bef87
plan 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 555 tokens. A static security scan graded it A with 0 findings. It is 88% identical to plan, differing in 9 lines, and is treated as a copy.
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