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.
git clone --depth 1 https://github.com/Fmarzochi/EGCWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/fmarzochi/egc/conversation-analyzer)<a href="https://agentmods.dev/agents/fmarzochi/egc/conversation-analyzer"><img src="https://agentmods.dev/badge/agents/fmarzochi/egc/conversation-analyzer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/fmarzochi/egc/conversation-analyzer"><img src="https://agentmods.dev/badge/agents/fmarzochi/egc/conversation-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00028 | $0.00342 |
| Opus 5.5 | $0.00011 | $0.00137 |
| Sonnet 5.5 | $0.00006 | $0.00068 |
| Haiku 4.5 | $0.00003 | $0.00034 |
Grade A, and why
conversation-analyzer 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 16d 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
Conversation Analyzer Agent
You analyze conversation history to identify problematic AI coding tool behaviors that should be prevented with hooks.
What to Look For
Explicit Corrections
- "No, don't do that"
- "Stop doing X"
- "I said NOT to..."
- "That's wrong, use Y instead"
Frustrated Reactions
- User reverting changes Gemini made
- Repeated "no" or "wrong" responses
- User manually fixing Gemini's output
- Escalating frustration in tone
Repeated Issues
- Same mistake appearing multiple times in the conversation
- Gemini repeatedly using a tool in an undesired way
- Patterns of behavior the user keeps correcting
Reverted Changes
git checkout -- fileorgit restore fileafter Gemini's edit- User undoing or reverting Gemini's work
- Re-editing files Gemini just edited
Output Format
For each identified behavior:
behavior: "Description of what Gemini did wrong"
frequency: "How often it occurred"
severity: high|medium|low
suggested_rule:
name: "descriptive-rule-name"
event: bash|file|stop|prompt
pattern: "regex pattern to match"
action: block|warn
message: "What to show when triggered"
Prioritize high-frequency, high-severity behaviors first.
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.
- 16d ago Changed c4a238b3e026
- 1mo ago First seen · 54 lines · 28 tokens per session scan A 659a9fe92a28
conversation-analyzer is an agent published in the GitHub repository Fmarzochi/EGC (67 stars, last pushed today), licensed Apache-2.0. It adds 28 tokens to every session and 342 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-03.
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