Borrowing it
Nothing to install: this file belongs to SimonBlancoE/kanban-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/SimonBlancoE/kanban-mcp/main/.claude/skills/kanban-review-loop/SKILL.mdgit clone --depth 1 https://github.com/SimonBlancoE/kanban-mcpWrote 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/skills/simonblancoe/kanban-mcp/kanban-review-loop)<a href="https://agentmods.dev/skills/simonblancoe/kanban-mcp/kanban-review-loop"><img src="https://agentmods.dev/badge/skills/simonblancoe/kanban-mcp/kanban-review-loop/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/skills/simonblancoe/kanban-mcp/kanban-review-loop"><img src="https://agentmods.dev/badge/skills/simonblancoe/kanban-mcp/kanban-review-loop.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 | $0.00027 | $0.01229 |
| Opus 5 | $0.00014 | $0.00615 |
| Sonnet 5 | $0.00005 | $0.00246 |
| Haiku 4.5 | $0.00003 | $0.00123 |
Grade A, and why
kanban-review-loop 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Kanban Review Loop - Continuous Health Monitoring
You are starting the Review Loop - a background daemon that continuously monitors Kanban board health with Ralph Wiggum awareness and session tracking for cross-context-window continuity.
Arguments
/kanban-review-loop- Start the daemon/kanban-review-loop stop- Stop (user should kill the background task)
Behavior
This runs as a background process that:
- Checks board health every 5 minutes
- Monitors escalated tasks (exceeded max iterations)
- Detects and reports issues
- Auto-spawns QA if review backlog grows
- Alerts on stale or blocked tasks
- Tracks sprint progress
- Generates session summaries for context bridging
Start the Daemon
Run in background using Task tool:
Task tool:
subagent_type: "general-purpose"
run_in_background: true
description: "Kanban review loop daemon"
prompt: [See daemon instructions below]
Daemon Instructions
You are the KANBAN REVIEW LOOP DAEMON with Ralph Wiggum awareness and session tracking.
## Main Loop (repeat continuously)
### Step 0: Session Check (once at start)
Start session: kanban_session_start with agentId: "review-loop-daemon"
This gives you context about recent activity and any continuity notes.
### Step 1: Board Health Verification
Run: kanban_verify_board_health
This returns structured health status with recommendation.
### Step 2: Full Health Check
Run: kanban_health_check with role: "architect", staleThresholdHours: 24
### Step 3: Check Escalations
Run: kanban_get_escalated_tasks with role: "architect"
### Step 4: Check Active Sprint
Run: kanban_sprint_list with role: "architect"
For each active sprint, check iteration count vs maxIterations.
### Step 5: Analyze & Alert
Check for issues:
**CRITICAL ALERTS:**
- **Escalated tasks** (exceeded maxIterations):
Log "CRITICAL: Task [title] escalated after [N] iterations - needs human review"
- **Critical tasks not started**:
Log "ALERT: Critical task [title] waiting"
**WARNING ALERTS:**
- **High iteration tasks** (iteration >= maxIterations - 1):
Log "WARNING: Task [title] at iteration [N]/[max] - at risk of escalation"
- **Stale tasks** (in_progress > 24h):
Log "WARNING: Task [title] stale for [hours]h"
- **Sprint at risk** (iteration near max):
Log "WARNING: Sprint [goal] at iteration [N]/[max]"
**INFO ALERTS:**
- **QA backlog > 3**:
Log "INFO: QA backlog high, spawning QA agent"
- **Overloaded agents** (> 5 tasks):
Log "INFO: Agent [id] overloaded with [N] tasks"
- **Low backlog** (< 3 tasks):
Log "INFO: Backlog low, plan more work"
### Step 6: Auto-Remediation
If QA backlog > 3, spawn QA agent (NOT in background):
Task tool: subagent_type: "general-purpose" prompt: | You are QA. Clear the backlog. 1. kanban_session_start with agentId: "qa-auto" 2. kanban_qa_list with role: "qa" 3. For each task: - kanban_get_task_detail to see iteration history - Review and approve/reject with structured feedback 4. kanban_session_end with summary
### Step 7: Generate Summary
Run: kanban_generate_summary
This updates the session-summary.md file for other agents.
### Step 8: Report Status
Output:
---
[TIME] Review Loop Check #N
Health: [OK | WARNING | CRITICAL]
Sprint Status:
- [Sprint goal]: Iteration [N]/[max] - [status]
Board:
- Backlog: X | In Progress: Y | Blocked: Z | Done: W
- Pending QA: Q
- Escalated: E
Issues:
- [list of alerts]
Actions Taken:
- [any remediation]
Next check in 5 minutes...
---
### Step 9: Sleep
Wait 5 minutes, then repeat from Step 1.
### On Shutdown
When loop is stopped:
kanban_session_end with: agentId: "review-loop-daemon" sessionNotes: "Review loop stopped. X checks performed." cleanState: true
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.
- 9d ago First seen · 178 lines · 27 tokens per session scan A 9fddb8e5dfc5
kanban-review-loop is a skill published in the GitHub repository SimonBlancoE/kanban-mcp (0 stars, last pushed 8mo ago), licensed MIT. It adds 27 tokens to every session and 1,229 once invoked, about $0.0001 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 2026-08-31.
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