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/agiflow/ai-plugin/backlog-groomingnpx skills add AgiFlow/ai-plugin --skill backlog-groominggit clone --depth 1 https://github.com/AgiFlow/ai-pluginWrote 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/agiflow/ai-plugin/backlog-grooming)<a href="https://agentmods.dev/skills/agiflow/ai-plugin/backlog-grooming"><img src="https://agentmods.dev/badge/skills/agiflow/ai-plugin/backlog-grooming.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 | $0.00055 | $0.00442 |
| Opus 5 | $0.00028 | $0.00221 |
| Sonnet 5 | $0.00011 | $0.00088 |
| Haiku 4.5 | $0.00006 | $0.00044 |
Grade A, and why
backlog-grooming 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 5d 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.
This is a copy
100% identical to backlog-grooming — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Agiflow Backlog Grooming
Treat grooming as the quality gate between Planning and Todo.
Workflow
- Resolve the target project and call
list_project_statusesto discover its exact status names. - Call
list_tasksfor Planning tasks,list_work_unitsfor existing active work units, andlist_membersfor assignment context. - Call
get_taskfor tasks whose readiness, dependencies, or acceptance criteria are unclear. - Classify every Planning task as:
- Ready
- Needs refinement
- Blocked by a dependency
- Duplicate or obsolete
- Require a clear outcome, sufficient context, and at least two testable acceptance criteria before promotion.
- Propose a priority order and explain the tradeoffs.
- Group three to eight cohesive tasks into a work unit only when they deliver one shared capability. Leave one or two related tasks standalone and split groups larger than eight.
- Review existing work units for shared dependencies and sequencing conflicts.
- Present the proposed promotions, work units, assignments, and dependency order. Request approval before writing.
- After approval:
- Use
batch_create_work_unitsfor approved groups. - Use
update_taskto move only ready, ungated tasks to the exact Todo status and set their ordering.
- Use
- Verify with
list_tasksandlist_work_units.
Guardrails
- Never promote a vague task or a task missing testable acceptance criteria.
- Never promote a downstream task whose required upstream work is incomplete.
- Do not force unrelated work into one work unit.
- Do not modify records before the user approves the proposed grooming plan.
- Recommend
refine-taskfor tasks that fail readiness checks.
Response
Report promoted tasks, created work units, items left in Planning, dependency gates, and the recommended execution order.
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.
- 5d ago First seen · 41 lines · 55 tokens per session scan A 911830f4ec48
backlog-grooming is a skill published in the GitHub repository AgiFlow/ai-plugin (3 stars, last pushed 1mo ago), licensed MIT. It adds 55 tokens to every session and 442 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to backlog-grooming, differing in 0 lines, and is treated as a copy.
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