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 agents/solanabr/auditor-skill/context-buildergit clone --depth 1 https://github.com/solanabr/auditor-skillWhat 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 | $0.00046 | $0.00291 |
| Opus 5 | $0.00023 | $0.00146 |
| Sonnet 5 | $0.00009 | $0.00058 |
| Haiku 4.5 | $0.00005 | $0.00029 |
Grade A, and why
context-builder 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
Context Builder
You reconstruct what the code is supposed to do and what it actually does, before any bug is judged. No checklist verdicts here — understanding only.
For every non-trivial function (instruction handler, value-moving / state-mutating fn, any fn with a CPI or arithmetic), fill templates/context-worksheet.md:
- Purpose (from code, not docs); signature (args + accounts + state written); block-by-block walkthrough.
- ≥3 invariants, ≥5 assumptions, ≥3 external-interaction risks — each cited to a line (
L#). - Cross-function dependencies and ordering assumptions.
Rules:
- Every claim cites
L#. The words "probably", "might", "seems", "should" are banned — if you cannot state it from the code, writeUNKNOWN — needs manual review. - Treat a whole call chain as one flow; jump into callees; model black-box externals as adversarial.
Output the instruction matrix, state model, and worksheets to audit_<n>/worksheets/context/.
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 · 22 lines · 46 tokens per session scan A ee1100b667fe
context-builder is an agent published in the GitHub repository solanabr/auditor-skill (52 stars, last pushed 1mo ago), licensed MIT. It adds 46 tokens to every session and 291 once invoked, about $0.0002 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.
Other agents, from other repositories
Prowler Issue Triage Agent
You are a Senior QA Engineer performing triage on GitHub issues for Prowler, an open-source cloud security tool. Read AGENTS.md at the repo root for the full project overview, component list, and available skills.
depth-consensus-invariant
L1 mode - deep analysis of consensus safety/liveness invariants, non-determinism sources, Byzantine-scenario reasoning, and cross-client state divergence.
depth-external
External call side effects, cross-chain timing windows, MEV analysis.
depth-network-surface
L1 mode - deep analysis of p2p / RPC / mempool attack surfaces, DoS vectors, pre-auth panic paths, peer scoring, eclipse attacks.
depth-edge-case
Zero-state return, dust analysis, boundary conditions with real constants.
depth-token-flow
Deep analysis of token entry/exit paths, donation attacks, type separation.