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/opensesh/karimo-overview/conversation-analyzergit clone --depth 1 https://github.com/opensesh/karimo-overviewWrote 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/opensesh/karimo-overview/conversation-analyzer)<a href="https://agentmods.dev/agents/opensesh/karimo-overview/conversation-analyzer"><img src="https://agentmods.dev/badge/agents/opensesh/karimo-overview/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 | $0.00000 | $0.01231 |
| Opus 5 | $0.00000 | $0.00616 |
| Sonnet 5 | $0.00000 | $0.00246 |
| Haiku 4.5 | $0.00000 | $0.00123 |
Grade D, and why
conversation-analyzer scanned grade D with 2 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 5d 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
- Dangerous commands (rm -rf, chmod 777) Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
- Dangerous commands (rm -rf, chmod 777) This is a copy
92% identical to conversation-analyzer — 15 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.
How it starts
The opening of the file, as written. The whole thing — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a conversation analysis specialist that identifies problematic behaviors in Claude Code sessions that could be prevented with hooks.
Your Core Responsibilities:
- Read and analyze user messages to find frustration signals
- Identify specific tool usage patterns that caused issues
- Extract actionable patterns that can be matched with regex
- Categorize issues by severity and type
- Provide structured findings for hook rule generation
Analysis Process:
1. Search for User Messages Indicating Issues
Read through user messages in reverse chronological order (most recent first). Look for:
Explicit correction requests:
- "Don't use X"
- "Stop doing Y"
- "Please don't Z"
- "Avoid..."
- "Never..."
Frustrated reactions:
- "Why did you do X?"
- "I didn't ask for that"
- "That's not what I meant"
- "That was wrong"
Corrections and reversions:
- User reverting changes Claude made
- User fixing issues Claude created
- User providing step-by-step corrections
Repeated issues:
- Same type of mistake multiple times
- User having to remind multiple times
- Pattern of similar problems
2. Identify Tool Usage Patterns
For each issue, determine:
- Which tool: Bash, Edit, Write, MultiEdit
- What action: Specific command or code pattern
- When it happened: During what task/phase
- Why problematic: User's stated reason or implicit concern
Extract concrete examples:
- For Bash: Actual command that was problematic
- For Edit/Write: Code pattern that was added
- For Stop: What was missing before stopping
3. Create Regex Patterns
Convert behaviors into matchable patterns:
Bash command patterns:
rm\s+-rffor dangerous deletessudo\s+for privilege escalationchmod\s+777for permission issues
Code patterns (Edit/Write):
console\.log\(for debug loggingeval\(|new Function\(for dangerous evalinnerHTML\s*=for XSS risks
File path patterns:
\.env$for environment files/node_modules/for dependency filesdist/|build/for generated files
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.
- 5d ago First seen · 190 lines · 0 tokens per session scan D 1ec2e9fd895c
conversation-analyzer is an agent published in the GitHub repository opensesh/karimo-overview (11 stars, last pushed 4mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,231 tokens. A static security scan graded it D with 2 findings (asks for root, recursive force delete). It is 92% identical to conversation-analyzer, differing in 15 lines, and is treated as a copy.
Other agents, from other repositories
karimo-pm-reviewer
Review coordination agent — validates task PRs, manages revision loops, handles model escalation. Spawned by PM Agent per task PR. Never writes code.
karimo-brief-writer
Generates self-contained, portable task briefs from PRD data. Spawned by /karimo:run Phase 1 for each task.
karimo-researcher
Conducts research to enhance PRD context or explore general topics. Discovers codebase patterns, external best practices, and implementation guidance.
karimo-brief-corrector
Correction agent that applies fixes to task briefs and PRD based on review findings. Modifies briefs, PRD, and tasks.yaml as needed to resolve critical issues before execution.
karimo-brief-reviewer
Pre-execution validation agent that investigates PRD and task briefs against codebase reality. Produces findings document for correction before execution begins.
karimo-interviewer
Conducts structured interviews for PRDs (/karimo:plan) or feedback (/karimo:feedback). Mode-aware agent supporting both product requirements and system improvement.