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/iLearn-Lab/EvoHarnessWrote 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/commands/ilearn-lab/evoharness/task-board)<a href="https://agentmods.dev/commands/ilearn-lab/evoharness/task-board"><img src="https://agentmods.dev/badge/commands/ilearn-lab/evoharness/task-board.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 | $0.00010 | $0.00125 |
| Opus 5 | $0.00005 | $0.00063 |
| Sonnet 5 | $0.00002 | $0.00025 |
| Haiku 4.5 | $0.00001 | $0.00013 |
Grade A, and why
task-board 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 3d 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.
The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
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.
- 3d ago First seen · 15 lines · 10 tokens per session scan A b2653cc187c3
task-board is a command published in the GitHub repository iLearn-Lab/EvoHarness (59 stars, last pushed 2mo ago), with no licence file. It adds 10 tokens to every session and 125 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 2026-09-03.
Other commands, from other repositories
speckit.taskstoissues
Convert existing tasks into actionable, dependency-ordered GitHub issues for the feature based on available design artifacts.
implement-plan
Implement the plan as specified, it is attached for your reference. Do NOT edit the plan file itself. Create todos for the plan as you work, starting with the first one. Don't stop until you have completed all the to-dos.
adoption-track
Tracking de adopción — comandos usados por rol, curva de aprendizaje, puntos de fricción.
ai-exposure-audit
Auditoría de exposición IA por rol — observed exposure, riesgo de desplazamiento, reskilling.
bias-check
Auditoría contrafactual de sesgos en asignaciones y comunicaciones del sprint.
confluence-publish
Publicar documentación del proyecto en Confluence. Convierte markdown a formato Confluence y crea/actualiza páginas en el espacio del proyecto.