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/raja21068/autoresearch/conversation-analyzergit clone --depth 1 https://github.com/raja21068/AutoResearchWrote 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/raja21068/autoresearch/conversation-analyzer)<a href="https://agentmods.dev/agents/raja21068/autoresearch/conversation-analyzer"><img src="https://agentmods.dev/badge/agents/raja21068/autoresearch/conversation-analyzer.svg" alt="Measured on agentmods" 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 | $0.00331 |
| Opus 5 | $0.00014 | $0.00166 |
| Sonnet 5 | $0.00006 | $0.00066 |
| Haiku 4.5 | $0.00003 | $0.00033 |
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 6d 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.
This is a copy
100% identical to conversation-analyzer — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Conversation Analyzer Agent
You analyze conversation history to identify problematic Claude Code 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 Claude made
- Repeated "no" or "wrong" responses
- User manually fixing Claude's output
- Escalating frustration in tone
Repeated Issues
- Same mistake appearing multiple times in the conversation
- Claude repeatedly using a tool in an undesired way
- Patterns of behavior the user keeps correcting
Reverted Changes
git checkout -- fileorgit restore fileafter Claude's edit- User undoing or reverting Claude's work
- Re-editing files Claude just edited
Output Format
For each identified behavior:
behavior: "Description of what Claude 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.
- 6d ago First seen · 53 lines · 28 tokens per session scan A 5c66b44d4e79
conversation-analyzer is an agent published in the GitHub repository raja21068/AutoResearch (2 stars, last pushed 3mo ago), licensed MIT. It adds 28 tokens to every session and 331 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to conversation-analyzer, differing in 0 lines, and is treated as a copy.
Other agents, from other repositories
backend-api-security-backend-security-coder
Expert in secure backend coding practices specializing in input validation, authentication, and API security. Use PROACTIVELY for backend security implementations or security code reviews.
data-engineer
Build scalable data pipelines, modern data warehouses, and real-time streaming architectures. Implements Apache Spark, dbt, Airflow, and cloud-native data platforms. Use PROACTIVELY for data pipeline design, analytics infrastructure, or modern data stack implementation.
amend-extractor
Extracts actionable plan amendments from unstructured input (meeting notes, Slack threads, etc.).
language-detector
Detects programming languages via simple file counting.
api-spec-writer
Produces api-requirements.md from an approved plan. Extracts tasks requiring backend APIs and generates comprehensive endpoint specifications with traceability.
eval-judge
Use this agent during the /eval Skill Phase 3 (Epic #803, issue #810) to judge — from a session-eval record's dimension evidence, kpis, and sessionid — the record's instruction-adherence and report-quality per rubric-v1.md's Judge Dimensions section. Dispatched read-only, coordinator-side (never inside a wave) by…