task-register

A workflow for registering a new task as a GitHub Issue in the Hyper-Waterfall project process. A GitHub Issue is a tracked work item containing the task details and its project labels or milestone.

In plain words
What is it for?
Searching existing Issues, reviewing milestones and labels, confirming the task details with the requester, creating the Issue, and handing it off to the project's tracking workflow.
Why use it?
It checks for duplicate tasks and confirms the proposed title, description, milestone, and labels before creating a new Issue.

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/postmelee/hyper-waterfall/task-register
Any agent
npx skills add postmelee/hyper-waterfall --skill task-register
Clone the repo
git clone --depth 1 https://github.com/postmelee/hyper-waterfall

Made for: Claude Code, Codex.

Per session 72 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,399 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 $0.00072 $0.01399
Opus 5 $0.00036 $0.00700
Sonnet 5 $0.00014 $0.00280
Haiku 4.5 $0.00007 $0.00140

Measured 3d ago against content hash 295ada15ff42, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

task-register 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.

templates/locales/en/mydocs/skills/task-register/SKILL.md · 129 lines

How it starts

The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Hyper-Waterfall Issue Registration

Trigger

  • The task requester explicitly asks to register an Issue, create a new task, or start from an Issue.
  • The task requester invokes this SKILL directly.

Preconditions

  • The work does not yet have an Issue number.
  • Purpose, background, and scope are at least drafted.
  • gh CLI is authenticated for the current user.
  • When possible, .github/ISSUE_TEMPLATE/task.yml or framework source templates/.github/ISSUE_TEMPLATE/task.yml can be read.
  • Before creating the Issue, the title, body, milestone, and label draft can be confirmed with the task requester.

Procedure

  1. Check for duplicate Issues.
    gh issue list --repo {REPO_SLUG} --state all \
      --search "{work keywords}" \
      --limit 20 \
      --json number,title,state,milestone,labels,url
    
    • If a substantially identical open Issue exists, do not create a new one. Ask whether to use the existing Issue.
    • If a closed Issue covered the same topic, link it in the new Issue references.
  2. Check open milestones.
    gh api repos/{REPO_SLUG}/milestones \
      --jq '.[] | {number,title,state,description,open_issues,closed_issues}'
    
    • Judge from the live title, state, and description.
    • Do not rely on remembered old milestone lists or version mappings.
  3. Check existing labels.
    gh api repos/{REPO_SLUG}/labels --paginate \
      --jq '.[] | {name,description,color}'
    
    • Judge from live name and description.
    • Do not rely on remembered old label lists.
  4. Choose milestone candidates.
    • Use only open milestones.
    • Compare work purpose, scope, component, and release phase with the milestone title and description.
    • If one candidate is clear, record its title and reason.
    • If 2-3 candidates are possible, present them with reasons and ask the task requester.
    • If no open milestone fits or descriptions are insufficient, ask the task requester instead of guessing.
  5. Choose label candidates.
    • Use only existing labels from the live lookup.
    • Select a label only when the work clearly matches the label name and description.
    • Prefer 1 type label, 1-2 area labels, and 0-1 kind/status label.
    • Type labels include bug, documentation, enhancement, duplicate, or question.
    • Area labels are selected by primary work ownership, not every affected area.
    • Kind labels such as kind:architecture, kind:automation, kind:regression, kind:verification, or kind:follow-up are used only when they meaningfully distinguish handling.
    • General Issues should usually have 2-4 labels.
    • If 5 or more labels are needed, write the exception reason in the draft and confirm it with the task requester.
    • If candidates are clear, record label names and reasons.
    • If no label fits or the fit is ambiguous, create without labels or ask the task requester.
    • Do not create new labels.
  6. Draft the Issue.
    • Title: one sentence that reveals the work unit.
    • Body: prefer GitHub Issue Form .github/ISSUE_TEMPLATE/task.yml.
      • In a framework repository, use templates/.github/ISSUE_TEMPLATE/task.yml when checking the source template for applied repositories.
      • Since gh issue create does not run Issue Form UI, convert form fields to Markdown sections.
    • Issue Form sections:
      • Background
      • Goals
      • Scope - Included
      • Scope - Excluded
      • Acceptance Criteria
      • Verification Criteria
      • References
      • Milestone and label candidates
    • If the Issue Form cannot be read, use the same section list as fallback.
    • Milestone: one open milestone chosen from live lookup and the selection reason.
    • Labels: approved existing labels and reasons, or none.
    • Split label reasons by type/area/kind, and include the exception reason if using 5 or more labels.
  7. Request approval before creating the Issue.
    • Show the task requester the title, body, milestone, labels, and selection reasons.
    • Do not run gh issue create until the task requester explicitly approves creation in the same thread.
  8. After approval, create the Issue.
    gh issue create --repo {REPO_SLUG} \
      --title "{title}" \
      --body "{body}" \
      --milestone "{milestone}" \
      --label "{label}"
    
    • Repeat --label for multiple labels, such as --label documentation --label enhancement.
    • Omit --label when creating without labels.
  9. Confirm the created Issue.
    gh issue view {N} --repo {REPO_SLUG} \
      --json number,title,state,milestone,labels,url
    
  10. Report the created Issue number and URL, then request approval to enter task-start.

Read the full file on GitHub · 129 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. 3d ago First seen · 129 lines · 72 tokens per session scan A 295ada15ff42

Subscribe to this mod's changes

task-register is a skill published in the GitHub repository postmelee/hyper-waterfall (78 stars, last pushed 1mo ago), licensed MIT. It adds 72 tokens to every session and 1,399 once invoked, about $0.0004 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 2026-08-30.

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