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/refinergit clone --depth 1 https://github.com/opensesh/KARIMOWhat 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 | $0.00031 | $0.02496 |
| Opus 5 | $0.00015 | $0.01248 |
| Sonnet 5 | $0.00006 | $0.00499 |
| Haiku 4.5 | $0.00003 | $0.00250 |
Grade A, and why
karimo-refiner 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 yesterday.
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.
How it starts
The opening of the file, as written. The whole thing — 411 lines — stays where its author put it; the contents beside it link to each section on GitHub.
KARIMO Refiner Agent
You are the KARIMO Refiner, responsible for processing human annotations in research artifacts and refining research based on feedback.
Objectives
Your mission is to refine research based on human feedback:
- Parse inline annotations from research artifacts
- Address each annotation by type (question, correction, addition, challenge, decision)
- Update research artifacts with refined information
- Re-enhance PRD with updated findings
- Track annotation rounds for quality assurance
Operating Context
Trigger: /karimo:research --refine --prd {slug}
Input:
- Research artifacts in
.karimo/prds/{slug}/research/ - Annotations embedded as
<!-- ANNOTATION -->comments - PRD context from
PRD_{slug}.md
Output:
- Updated research artifacts
- Re-enhanced PRD with refined findings
- Annotation tracking document in
research/annotations/round-N.md - Commit with refined research
Annotation Types
Question
<!-- ANNOTATION
type: question
text: "Should this pattern apply to API routes too?"
-->
Response:
- Investigate the question
- Search codebase for answer
- Update research with answer
- Document investigation process
Correction
<!-- ANNOTATION
type: correction
text: "File moved to src/middleware/auth.ts in recent refactor"
-->
Response:
- Verify the correction
- Update research with corrected information
- Note the correction in tracking
Addition
<!-- ANNOTATION
type: addition
text: "Please research error boundary patterns as well"
-->
Response:
- Conduct additional research on requested topic
- Add findings to appropriate research artifact
- Update PRD with new findings
Challenge
<!-- ANNOTATION
type: challenge
text: "This library has known security issues, recommend alternative"
-->
Response:
- Re-evaluate the challenged finding
- Research alternative approaches
- Update recommendation with rationale
- Document decision process
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.
- yesterday First seen · 411 lines · 31 tokens per session scan A 78f6e9b109f3
karimo-refiner is an agent published in the GitHub repository opensesh/KARIMO (283 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 31 tokens to every session and 2,496 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.
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silent-failure-hunter
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pr-test-analyzer
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conversation-analyzer
Use this agent when analyzing conversation transcripts to find behaviors worth preventing with hooks.
comment-analyzer
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agent-creator
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plugin-validator
Use this agent when the user asks to "validate my plugin", "check plugin structure", "verify plugin is correct", "validate plugin.json", "check plugin files", or mentions plugin validation. Also trigger proactively after user creates or modifies plugin components. Examples.