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/bnet47/codexicon/investigatenpx skills add bnet47/codexicon --skill investigategit clone --depth 1 https://github.com/bnet47/codexiconWhat 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 | $0.00030 | $0.00360 |
| Opus 5 | $0.00015 | $0.00180 |
| Sonnet 5 | $0.00006 | $0.00072 |
| Haiku 4.5 | $0.00003 | $0.00036 |
Grade A, and why
investigate 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 3d 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
Investigate
Announce: "I'm using investigate to identify the root cause before changing behavior."
1. Define the symptom
Capture the expected behavior, actual behavior, environment, and smallest known failing command or interaction. Preserve the exact error text.
2. Reproduce
Run or create the smallest safe reproduction. If reproduction is impossible, gather the strongest available evidence and label conclusions accordingly; do not claim certainty.
3. Form hypotheses
List two to four plausible causes ranked by likelihood. For each, identify the observation that would confirm or reject it.
4. Isolate
Test one hypothesis at a time with read-only inspection or the smallest reversible diagnostic. Avoid changing several variables together. Keep notes on evidence and eliminate contradicted hypotheses.
5. Conclude
State the root cause in one sentence with the causal chain and evidence. Distinguish the initiating defect from downstream symptoms.
If the user asked only to diagnose, stop here and recommend a fix plus verification. If the user asked to fix, implement the smallest root-cause correction, add a regression test, rerun the original reproduction, then run the relevant full checks.
Report
## Investigation: [symptom]
**Reproduction:** `[command]` — [result]
**Root cause:** [one sentence]
**Evidence:** [observations that isolate it]
**Fix:** [implemented change or recommended correction]
**Verification:** [commands and results, if implemented]
**Uncertainty:** [remaining limitation, or none]
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.
- 3d ago First seen · 45 lines · 30 tokens per session scan A 090c520c755c
investigate is a skill published in the GitHub repository bnet47/codexicon (5 stars, last pushed 4d ago), licensed MIT. It adds 30 tokens to every session and 360 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 2026-08-31.
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