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 skills/s3yed/appie-kit/kanbannpx skills add S3YED/appie-kit --skill kanbangit clone --depth 1 https://github.com/S3YED/appie-kitWrote 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/s3yed/appie-kit/kanban)<a href="https://agentmods.dev/skills/s3yed/appie-kit/kanban"><img src="https://agentmods.dev/badge/skills/s3yed/appie-kit/kanban.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 | $0.00031 | $0.01900 |
| Opus 5 | $0.00015 | $0.00950 |
| Sonnet 5 | $0.00006 | $0.00380 |
| Haiku 4.5 | $0.00003 | $0.00190 |
Grade A, and why
kanban 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 2d 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 — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Kanban Multi-Agent Workflow
Overview
Hermes Kanban is a durable SQLite board for multi-profile / multi-worker collaboration. Two roles:
- Orchestrator — decomposes goals into tasks, assigns to specialist profiles, routes and tracks
- Worker — picks up assigned tasks, does the work, completes or blocks with handoff context
The core worker lifecycle (including the kanban_create fan-out pattern and "decompose, don't execute" rule) is auto-injected into every kanban process via the KANBAN_GUIDANCE system-prompt block. This skill provides the deeper playbook for both roles.
Part A: Orchestrator Playbook
Profiles are user-configured — not a fixed roster
There is no default specialist roster. The orchestrator skill does not know what profiles exist on this machine. The dispatcher silently fails to spawn unknown assignee names.
Step 0: discover available profiles before planning.
hermes profile list # prints available profiles
kanban_list(assignee="<some-name>") # sanity-check a single name
# Or just ask the user
When to use the board
Create Kanban tasks when:
- Multiple specialists are needed
- The work should survive a crash or restart
- The user might want to interject
- Multiple subtasks can run in parallel
- Review / iteration is expected
- The audit trail matters
If none apply — use delegate_task instead or answer directly.
Anti-Temptation Rules
- Do not execute the work yourself — create a task for the right specialist
- Split multi-lane requests before creating cards
- Run independent lanes in parallel
- Never create dependent work as independent ready cards — use
parents=[...] - If no specialist fits, ask the user — don't invent profile names
Decomposition Playbook
Step 1 — Understand the goal. Ask clarifying questions if ambiguous.
Step 2 — Sketch the task graph. Extract lanes, map to profiles, decide dependencies. Show the graph to the user before creating cards.
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.
- 2d ago First seen · 203 lines · 31 tokens per session scan A 4213b29d9e35
kanban is a skill published in the GitHub repository S3YED/appie-kit (7 stars, last pushed 10d ago), licensed MIT. It adds 31 tokens to every session and 1,900 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 2026-09-03.
Other skills, from other repositories
seo-geo-optimizer
Comprehensive SEO/GEO/AEO analysis toolkit for optimizing content visibility across traditional search engines (Google, Bing), AI platforms (ChatGPT, Perplexity, Claude, Gemini, Grokipedia), answer engines (Google AI Overviews, Bing Copilot, featured snippets), voice assistants (Google Assistant, Siri, Alexa), and…
internal-linking-optimizer
Use when improving internal link structure, anchor text, orphan pages, crawl depth, site architecture, or link equity flow. 内链优化/站内架构.
geo-review-html
Render an interactive, self-contained HTML companion for a GEO content brief (04-content-brief) or a publish-ready draft (05-production), so a NON-technical client reviewer (founder, organizer staff, the domain expert filling slots) can fill REQUIRED-FILL slots, leave section-level comments, and approve/return work in…
geo-pipeline
Entry point + orchestrator for the recomby-geo GEO (Generative Engine Optimization) workflow on OpenAI Codex CLI. Use when the user wants to run any stage of the GEO pipeline on a client folder — intake, visibility audit, content-gap analysis, content brief, draft production, distribution, or monthly re-audit — or…
follow-up-writer
Use when drafting a post-event follow-up message to someone met at a conference.
schedule
Create, list, remove or inspect this bot's scheduled work — recurring jobs ("every morning at 7 tell me X", "every weekday at 9 post the standup") and one-shot follow-ups ("check back in 20 minutes", "watch that deploy until it lands", "remind me on Friday"). Use whenever something must happen on a schedule…