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/capatinore/contextforge-mcp/cf-analyzegit clone --depth 1 https://github.com/capatinore/contextforge-mcpWhat 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 | $0.00164 |
| Opus 5 | $0.00000 | $0.00082 |
| Sonnet 5 | $0.00000 | $0.00033 |
| Haiku 4.5 | $0.00000 | $0.00016 |
Grade A, and why
cf-analyze scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
/speckit.cf-analyze
Analyze the existing codebase and compress the current spec before planning.
Run after /speckit.specify, before /speckit.plan.
Steps
cf_read_spec()— load and compress the current speccbm_search_graph(name_pattern="<pattern from spec>")— find related codecbm_get_architecture()— understand where the feature fitscbm_find_similar_code(node_id="<key node>")— avoid duplicating existing codecbm_get_impact(node_id="<key node>")— identify risk areas- Write
specs/$FEATURE_ID/context.mdwith findings cf_stats()— report token savings
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 · 15 lines · 0 tokens per session scan A 7a627b889338
cf-analyze is a command published in the GitHub repository capatinore/contextforge-mcp (4 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 164 tokens. 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
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.