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 skills/griffinwork40/agent-framework/appmapnpx skills add griffinwork40/agent-framework --skill appmapgit clone --depth 1 https://github.com/griffinwork40/agent-frameworkWhat 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 | $0.00023 | $0.00292 |
| Opus 5 | $0.00012 | $0.00146 |
| Sonnet 5 | $0.00005 | $0.00058 |
| Haiku 4.5 | $0.00002 | $0.00029 |
Grade A, and why
appmap scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Sub-agent contract
!awk '/^---$/{c++; next} c>=2' "${CLAUDE_SKILL_DIR}/../contract/SKILL.md"
Wave 1 (parallel): Dispatch two sub-agents. One maps the $ARGUMENT UI in Chrome: navigation structure, key pages/forms, interaction patterns, CSS selectors, and automatable workflows. The other researches $ARGUMENT's public API, docs, authentication, rate limits, and architectural patterns. Both return structured findings.
Synthesis: Merge Wave 1 outputs into a skill plan: list of automatable workflows (with interaction patterns and selectors), recommended API calls to supplement UI workflows, and implementation priorities.
Wave 2 (parallel): For each top-priority workflow, dispatch a sub-agent to implement it in the generated skill and unit-test it against the live UI. Agents operate in isolated tabs and return pass/fail results per workflow.
Verification: One final sub-agent runs the complete generated skill end-to-end against $ARGUMENT, validating all workflows together. If any workflow fails, re-dispatch failing workflow agents in Wave 2 and re-verify (max 2 retries; after that, report partial results with failing workflows noted).
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 · 17 lines · 23 tokens per session scan A e94c178a02c3
appmap is a skill published in the GitHub repository griffinwork40/agent-framework (23 stars, last pushed 7d ago), licensed Apache-2.0. It adds 23 tokens to every session and 292 once invoked, about $0.0001 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 2026-08-30.
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