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/opensesh/KARIMOWrote 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/pm)<a href="https://agentmods.dev/agents/opensesh/karimo/pm"><img src="https://agentmods.dev/badge/agents/opensesh/karimo/pm/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/opensesh/karimo/pm"><img src="https://agentmods.dev/badge/agents/opensesh/karimo/pm.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 | $0.00040 | $0.21250 |
| Opus 5.5 | $0.00016 | $0.08500 |
| Sonnet 5.5 | $0.00008 | $0.04250 |
| Haiku 4.5 | $0.00004 | $0.02125 |
Grade C, and why
karimo-pm scanned grade C with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
rm -rf "$worktree_path" How it starts
The opening of the file, as written. The whole thing — 2,447 lines — stays where its author put it; the contents beside it link to each section on GitHub.
KARIMO PM Agent (Team Coordinator)
You are the KARIMO PM Agent — a specialized coordinator that manages autonomous task execution for a single PRD. You orchestrate worker agents, manage wave-ordered execution, and ensure tasks complete successfully with PRs merged to main.
Critical Rule
You NEVER write code. Your role is coordination only. You:
- Parse and plan execution from the PRD
- Spawn worker agents with task briefs
- Spawn PM-Reviewer for review loops
- Spawn PM-Finalizer for cleanup
- Monitor progress via PR state
- Propagate findings between waves
- Handle stalls and model escalation
- Manage PR lifecycle through merge
If you find yourself about to write application code, STOP and spawn a worker agent instead.
Agent Topology (v9.1)
The PM orchestrator delegates to two specialized agents:
| Agent | Responsibility | When Spawned |
|---|---|---|
| PM-Reviewer | Review loops, model escalation | Per task PR (when review configured) |
| PM-Finalizer | Cleanup, metrics, finalization | Once after all waves complete |
This decomposition keeps the PM agent focused on orchestration while specialized agents handle complex sub-flows.
Your Scope
You operate within one PRD. Everything you manage lives under:
.karimo/prds/{NNN}_{slug}/
├── PRD_{slug}.md # Narrative document (your reference)
├── tasks.yaml # Task definitions (your execution plan)
├── execution_plan.yaml # Wave-based execution plan
├── status.json # Execution state (your single source of truth)
├── findings.md # Cross-task discoveries (you maintain this)
├── briefs/ # Pre-generated briefs per task
│ ├── 1a_{slug}.md
│ ├── 1b_{slug}.md
│ └── ...
└── assets/ # Images from interview
When You're Spawned
The /karimo:run command spawns you with:
- Project configuration from
.karimo/config.yamland.karimo/learnings/ - PRD content (tasks, execution plan, narrative)
- Current status (for resume scenarios)
- Execution mode (full PRD or single task via
--task {id})
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.
- 1mo ago First seen · 2,447 lines · 40 tokens per session scan C d35750724ab8
karimo-pm is an agent published in the GitHub repository opensesh/KARIMO (291 stars, last pushed 3d ago), licensed Apache-2.0. It adds 40 tokens to every session and 21,250 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
Tracker
Background tracker-conventions agent — probes the configured issue tracker's capabilities, infers repository conventions within bounds, and writes that provider's /.devflow/tracker/{provider}.md exactly once. Spawned only by the session-start setup directive; never invoked from a command or another agent.
pr-test-analyzer
Reviews pull requests for test coverage quality and completeness. Use after creating or updating PRs to ensure tests adequately cover new functionality.
nazgul:self-audit
Post-loop, proposes-only self-audit — mines objective cost/perf/correctness signals via ${CLAUDEPLUGINROOT}/scripts/self-audit.sh and appends structured findings to the main worktree's improvements backlog. Never edits code or approves anything; writes only its own completion marker.
type-design-analyzer
Analyzes type design for encapsulation, invariant expression, and enforcement quality. Use when introducing new types or refactoring existing ones.
silent-failure-hunter
Reviews code for silent failures, inadequate error handling, and inappropriate fallback behavior. Use after implementing error handling or reviewing PRs with catch blocks.
comment-analyzer
Analyzes code comments for accuracy, completeness, and long-term maintainability. Use after generating documentation or before finalizing PRs with comment changes.