Borrowing it
Nothing to install: this file belongs to causify-ai/helpers. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/causify-ai/helpers/master/.claude/skills/todo.reorg_headers/SKILL.mdgit clone --depth 1 https://github.com/causify-ai/helpersWrote 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/causify-ai/helpers/todo.reorg_headers)<a href="https://agentmods.dev/skills/causify-ai/helpers/todo.reorg_headers"><img src="https://agentmods.dev/badge/skills/causify-ai/helpers/todo.reorg_headers/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/causify-ai/helpers/todo.reorg_headers"><img src="https://agentmods.dev/badge/skills/causify-ai/helpers/todo.reorg_headers.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 | $0.00034 | $0.01064 |
| Opus 5.5 | $0.00014 | $0.00426 |
| Sonnet 5.5 | $0.00007 | $0.00213 |
| Haiku 4.5 | $0.00003 | $0.00106 |
Grade A, and why
todo.reorg_headers 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 29d 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Goal
- Align the H2 topic headers in
ai_task_queue.mdwith the canonical list inai_task_queue.md's# ALL TOPICSsection - Fold in stray H2 topics: either add them to
# ALL TOPICSin the right place, or merge them into an existing topic - Move each H3 task under the correct H2 topic, without moving it out of its current H1 stage
- Normalize every H3 task header to carry a checkbox marker, without changing markers that already exist
References
.claude/skills/todo.rules.md: defines the H1 stage / H2 topic / H3 task organization and the# ALL TOPICSmaster list
Workflow
Load the Conventions
- Read
.claude/skills/todo.rules.md - Read
ai_task_queue.md's# ALL TOPICSsection; record the ordered list of## <Topic>headers, keeping the// <group>comment lines as group boundaries (they mark where a topic belongs, they are not topics themselves)
Reconcile the Topic Taxonomy
- For every other H1 stage in
ai_task_queue.md(IN PROGRESS,HIGH PRIORITY,BACKLOG,ICEBOX, ...) list its H2 headers - For each H2 header, check whether it matches (case-insensitively) an ALL TOPICS
entry
- Match -> keep it, using the exact ALL TOPICS spelling as the canonical header
- No match -> decide:
- If it clearly restates or overlaps an existing ALL TOPICS entry (e.g. "Build & Infrastructure" vs "Build is green"), merge: rename its header to the existing entry and fold its tasks under that topic
- If it is a genuinely new topic, add it to
# ALL TOPICSunder the closest matching// <group>comment (or a new group if none fits), then keep it as its own H2 - Placeholder headers with no descriptive name (e.g.
## ?) are never kept: classify every task under them individually by content instead of by header
- Do not guess silently on an ambiguous case: list it and ask the user to pick the merge target vs. a new topic before proceeding
- Apply merges/additions to
# ALL TOPICSfirst, so the rest of the pass has one final taxonomy to file tasks against
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.
- 29d ago First seen · 91 lines · 34 tokens per session scan A 01c7b52fd9be
todo.reorg_headers is a skill published in the GitHub repository causify-ai/helpers (150 stars, last pushed today), licensed Apache-2.0. It adds 34 tokens to every session and 1,064 once invoked, about $0.0001 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 2026-09-18.
Other skills, from other repositories
story-readiness
Is a story implementation-ready? Checks clear acceptance criteria, open questions, ADR refs. READY/NEEDS WORK/BLOCKED/NOT ASSESSED.
recipe-create-meet-space
Create a Google Meet meeting space and share the join link.
workthreads
SpecStory Workthreads - a weekly work-thread rollup across a team's repos from SpecStory coding histories (any agent - Claude Code, Codex, Cursor, Gemini, and more). It groups the window's sessions into threads of work per project and labels each new / open / recently closed, so a lead sees what shipped, what is still…
atmos-config
Atmos root configuration: atmos.yaml discovery, precedence, deep merging, basepath, imports, minimal bootstrap, and routing to narrower Atmos skills.
ring:mapping-feature-relationships
Mapping how features relate and phasing the work: categorizing PRD features, grouping them into domains, charting cross-feature journeys, dependencies, and integration points, and defining the binding Phases that plan.md mirrors one-to-one at Gate 7. Gate 2 of ring:planning-large-features; runs after…
handle-linkedin-connection-request-signal
Use this skill when someone sends a team member an inbound LinkedIn connection request. An inbound request is a deliberate, ACTIVE first-party intent signal — meaningfully stronger than a passive profile view — and it deserves different scoring rules. The skill resolves and enriches the requester, gates them through…