refine

A backlog review that checks pending tasks for clarity, priority, dependencies, missing specifications, and age. A backlog is a list of work that has not been completed yet.

In plain words
What is it for?
Use it to groom, clean up, or improve a task backlog. It reviews pending tasks and suggests clearer descriptions, priorities, dependencies, and supporting specifications.
Why use it?
It helps turn vague or outdated work items into tasks that someone can act on. It also highlights ordering problems, such as tests that depend on unfinished features.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/backloghq/backlog/refine
Any agent
npx skills add backloghq/backlog --skill refine
Clone the repo
git clone --depth 1 https://github.com/backloghq/backlog

Made for: Claude Code, Codex.

Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 529 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00046 $0.00529
Opus 5 $0.00023 $0.00264
Sonnet 5 $0.00009 $0.00106
Haiku 4.5 $0.00005 $0.00053

Measured 2d ago against content hash 736e4d094efc, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

refine 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.

skills/refine/SKILL.md · 38 lines

How it starts

The opening of the file, as written. The whole thing — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Refine Backlog

Review the current backlog and improve its quality. This is a grooming pass — make tasks actionable, well-prioritized, and properly connected.

Process

  1. Load the backlog — call task_list with filter status:pending to get all pending tasks.

  2. Analyze each task for these issues:

    Vague descriptions — tasks that are too broad or unclear. A good description starts with a verb and is specific enough that someone could implement it without asking questions. Flag tasks that need to be broken down or clarified.

    Missing priorities — tasks without H/M/L priority. Suggest a priority based on the task's description and context.

    Missing dependencies — tasks that logically depend on other tasks but don't have depends set. Look for ordering constraints (e.g., "write tests" should depend on the feature it tests).

    Tasks needing specs — complex tasks (multi-step, architectural, or ambiguous) that don't have a doc attached. Check with task_count filter +doc status:pending and identify which tasks SHOULD have specs but don't.

    Stale tasks — tasks created long ago with no activity. Check entry dates and annotations. Flag anything older than 30 days with no progress.

    Urgency mismatches — tasks with high urgency scores but low priority, or vice versa. These might need priority adjustments.

  3. Present findings — group issues by category. For each issue, show the task ID, description, and the specific problem.

  4. Fix with permission — for each category, ask if the user wants to apply the suggested fixes. Use the UUIDs from the task_list response in step 1 for every task_modify / task_doc_write / task_annotate call — do not paraphrase or reuse UUIDs from earlier conversations. If you're unsure whether a UUID is still valid (e.g. after a long discussion), re-query with task_info before mutating.

Guidelines

  • Don't create new tasks — refinement improves existing ones
  • Don't delete tasks — flag stale ones for the user to decide
  • Suggest specific fixes, don't just list problems
  • If the backlog is small and clean, say so — don't invent issues

Read the full file on GitHub · 38 lines

Changes

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.

  1. 2d ago First seen · 38 lines · 46 tokens per session scan A 736e4d094efc

Subscribe to this mod's changes

refine is a skill published in the GitHub repository backloghq/backlog (5 stars, last pushed 3mo ago), licensed MIT. It adds 46 tokens to every session and 529 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 2026-08-31.

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