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 skills add ShaftHQ/SHAFT_ENGINE --skill kanbangit clone --depth 1 https://github.com/ShaftHQ/SHAFT_ENGINEWrote 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/shafthq/shaft_engine/kanban)<a href="https://agentmods.dev/skills/shafthq/shaft_engine/kanban"><img src="https://agentmods.dev/badge/skills/shafthq/shaft_engine/kanban/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/shafthq/shaft_engine/kanban"><img src="https://agentmods.dev/badge/skills/shafthq/shaft_engine/kanban.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 | $0.00918 |
| Opus 5.5 | $0.00016 | $0.00367 |
| Sonnet 5.5 | $0.00008 | $0.00184 |
| Haiku 4.5 | $0.00004 | $0.00092 |
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 13d 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Kanban task flow
Use when work has more than one deliverable, more than one ticket, or any delegate. Flow beats busyness: finish before starting.
Board
Keep one board per task as JSON (models corrupt JSON less than prose) in the session state directory, never in tracked files:
{"wip": {"doing": 1, "review": 2},
"cards": [{"id": "T1", "title": "...", "column": "ready",
"acceptance": ["..."], "proof": "command that proves it",
"evidence": null, "pr": null}]}
Columns: backlog -> ready -> doing -> review -> done.
readyrequires acceptance criteria and a proof command. No criteria, no pull.doingWIP 1 writer per repository: one card being edited at a time.reviewWIP 2: at two cards waiting for review or CI, pull nothing new.doneonly when the Definition of Done holds.
Pull rule
Every session, turn, and wake starts by draining right to left: open PRs and
review (red or ACTION_REQUIRED checks, behind base, conflicts, review
comments, auto-merge off), then doing, then shipped bugs or red default
branch. Pull a new ready card only when nothing downstream is actionable, and
only while review has capacity; waiting on CI counts as idle. Never leave a
started card to start another. Never push work forward. Group related cards
into the fewest safe pull requests. Avoid PRs that depend on other open PRs;
land them in order and merge base once before the final push.
Definition of Done
A card is done when all hold:
- Every acceptance criterion is met and its proof command output is attached.
- Tests for new behavior were red first, then green.
- One fresh-context review is clean; a second round only for blocker findings.
- Required checks are green on the exact head after one blocking wait per push
(
gh pr checks --watch --fail-fastorgh run watch); retry once, then stop and report. Never re-verify what already passed. - Every finding raised while working is closed (see below), including static-analysis and code-quality review threads (fix or reply, then resolve) before the PR counts as ready.
- Merged or handed off as instructed; worktree cleaned.
- After any CE harness change merges, every agent and delegate reloads the
latest harness from main before continuing. After each completed delivery
run
python3 .chaos-engine/tool.py maintain(fast-forward with local edits kept, reinstall, doctor, stale-store refresh, reload). - Ship to-deliver items in the fewest pull requests; group related issues.
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.
- 13d ago Changed · +10 lines 566c80cee08d
- 14d ago Changed · +6 lines 96142097cc38
- 15d ago First seen · 74 lines · 40 tokens per session scan A 9a6c9d1c39f1
kanban is a skill published in the GitHub repository ShaftHQ/SHAFT_ENGINE (414 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 918 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-02.
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