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 skills add OneWave-AI/claude-skills --skill meeting-to-tasksgit clone --depth 1 https://github.com/OneWave-AI/claude-skillsWrote 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/onewave-ai/claude-skills/meeting-to-tasks)<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/meeting-to-tasks"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/meeting-to-tasks/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/onewave-ai/claude-skills/meeting-to-tasks"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/meeting-to-tasks.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00045 | $0.00854 |
| Opus 5 | $0.00023 | $0.00427 |
| Sonnet 5 | $0.00009 | $0.00171 |
| Haiku 4.5 | $0.00005 | $0.00085 |
Grade A, and why
meeting-to-tasks 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 9d 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 — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meeting to Tasks
Transform raw meeting transcripts into structured, actionable outputs: decisions, action items, owners, deadlines, and open questions -- including implicit commitments participants may not realize they made.
Contents
references/extraction-schema.md-- YAML field schemas for every extraction phasereferences/markers.md-- Decision/action/implicit markers, priority + deadline inference, confidence scoringreferences/output-templates.md-- Meeting summary, task files (Linear/GitHub/generic), follow-up email, directory layoutreferences/meeting-types.md-- Meeting-type detection and per-type focus
Workflow
- Accept input. Handle plain text, Markdown, pasted text, audio transcript exports (Otter.ai, Fireflies, Rev, Zoom, Google Meet, Microsoft Teams), or structured notes.
- Validate. Confirm there is enough content (~100 words minimum), identifiable speakers, a discernible topic, and any timestamps. If input is too sparse, ask for the full transcript, the participant list, or the meeting purpose before proceeding.
- Read the full transcript first. Do not extract from a partial read -- later context can change earlier interpretation.
- Detect the meeting type and adjust focus per
references/meeting-types.md. - Extract in phases using the schemas in
references/extraction-schema.md: metadata, decisions, action items, open questions, parking lot, discussion points. Apply the markers and inference rules inreferences/markers.md. Preserve the exact source quote for every item. - Identify speakers. Build the participant list from speaker labels and track who said what. When labels are absent, infer from context clues, otherwise mark "Unassigned" and flag for the user to assign.
- Score confidence on every item (high/medium/low). Flag all low-confidence items for human review per
references/markers.md. - Resolve conflicts and ambiguity: flag contradictory commitments as "CONFLICT" with both versions; list all candidates for unclear ownership; translate vague deadlines ("soon", "ASAP") to specific dates and flag for confirmation; offer both readings of ambiguous scope; consolidate duplicates.
- Generate outputs using
references/output-templates.md. Confirm which project management format(s) the user wants before generating task files. Always generate the follow-up email, even if unasked. - Post-process: deduplicate overlapping items; map dependencies; highlight the critical path; report owner imbalance; warn on deadline clustering; list items missing owners or deadlines.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 50 lines · 45 tokens per session scan A aa2761eedbe6
meeting-to-tasks is a skill published in the GitHub repository OneWave-AI/claude-skills (291 stars, last pushed 1mo ago), licensed MIT. It adds 45 tokens to every session and 854 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 2026-09-03.
Other skills, from other repositories
after-action-report
Run a structured after-action review (postmortem, retrospective) on a launch, incident, or completed project to capture timeline, root cause analysis, contributing factors, and actionable lessons. Use this skill whenever the user wants to run a postmortem, retrospective, AAR, or after-action review on any past event.…
stakeholder-communication
Communicate effectively with stakeholders across functions and seniority levels. Use this skill when writing status updates, preparing executive reviews, sharing technical decisions with non-technical audiences, managing up, communicating bad news, or designing the communication cadence for a project. Triggers on…
mass-ulw
Drives dependency-ordered child work through the native workflow tool, one run per phase with retry/amend/send recovery. Use when the user asks for mass-ulw, a DAG of tasks, or fan-out work where some tasks must wait on others.
beta-program-management
Running closed and open betas that produce real signal. Beta participant selection, structured feedback collection, beta-to-GA decision criteria, and the difference between soft-launch (no structure, no signal), kitchen-sink (everyone in, no actionable feedback), and structured beta (calibrated cohort, intentional…
okr-design
OKR design as actually shipped, not as conference-talk theory. Outcome statements that drive decisions, key results that measure the right thing, scoring discipline, mid-quarter recalibration, and the difference between sandbagged OKRs (always 100%) and aspirational OKRs (always 30%) and stretch OKRs (genuine ambition…
roadmap-planning
Build a multi-quarter roadmap from a backlog of ideas, requests, and ongoing initiatives. Use this skill when planning the next quarter, sequencing dependent work, balancing build vs improve vs maintain, or making the case for what NOT to do. Triggers on roadmap, quarterly planning, what should we build next…