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 sutchan/Agent-Skills-Hub --skill descriptgit clone --depth 1 https://github.com/sutchan/Agent-Skills-HubWrote 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/sutchan/agent-skills-hub/descript)<a href="https://agentmods.dev/skills/sutchan/agent-skills-hub/descript"><img src="https://agentmods.dev/badge/skills/sutchan/agent-skills-hub/descript/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/sutchan/agent-skills-hub/descript"><img src="https://agentmods.dev/badge/skills/sutchan/agent-skills-hub/descript.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 | $0.00111 | $0.01927 |
| Opus 5 | $0.00056 | $0.00963 |
| Sonnet 5 | $0.00022 | $0.00385 |
| Haiku 4.5 | $0.00011 | $0.00193 |
Grade A, and why
descript 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 8d 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
91% identical to descript — 20 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.
How it starts
The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
descript
The talk-content editing tool skill — write the edit in the transcript, Overdub with consent, refine the
sound, dress the visuals, and ship the cuts. The agent plans (and can drive Underlord via API/MCP where
connected); the human verifies by ear and approves; WoopSocial publishes the exports. (Ships with
tools/integrations/descript.md.)
The POV: the transcript is the timeline — decide in text, verify by ear
For dialogue-heavy content, editing the transcript beats scrubbing a timeline: delete the sentence, the clip disappears; move the paragraph, the footage follows — reviews report ~60–70% editing-time cuts for talk content. But the paradigm has two sharp edges the top 1% respect. (1) The voice spine: Overdub's consent-verified, own-voice-only design is the model, not an obstacle — it exists so nobody types words into someone else's mouth; and the craft truth is it shines on flubbed words, not paragraphs (long Overdub drifts synthetic — re-record those). (2) The meaning spine: text-editing makes it dangerously easy to rearrange a guest into saying something they didn't — concision yes, meaning-flips never, and the human owns the final cut of anyone else's words. Operationally: the accuracy pass is mandatory (transcript errors become wrong edits AND wrong captions), and since the Sept 2025 overhaul, the workflow must be credit-aware — media minutes count everything you import, and formerly-unlimited AI features are metered.
Read these first
- The recording's content skill — podcast-and-audiograms / youtube-long-form / educational-content.
- brand-profile + voice-builder (written outputs) + design-and-templates (captions/layout).
The framework: WORDS
(Depth: references/the-words-framework.md.)
- W — Write the edit: accuracy pass first; then cut tangents/bad takes, one-step filler+silence removal (Underlord), restructure by moving paragraphs — decide in text, verify by ear.
- O — Overdub with consent: own-voice-only, consent-verified; single words/short phrases (paragraphs = re-record); vocabulary/credit limits; disclose synthetic speech where required.
- R — Refine the sound: Studio Sound once per source (credits; cleaner audio also improves the transcript); level speakers; extreme noise is a re-record, not a rescue.
- D — Dress the visuals: Automatic Multicam (record separate tracks on purpose), captions from the corrected transcript, human-approved B-roll, Eye Contact used honestly; beat-sync/color route elsewhere.
- S — Ship the cuts: one transcript → the episode + clips (Underlord flags, the human picks fairly) + show notes + chapters + a text post; route onward and publish via WoopSocial.
What ships with it
5 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.
- 8d ago First seen · 99 lines · 111 tokens per session scan A ad4ce602651f
descript is a skill published in the GitHub repository sutchan/Agent-Skills-Hub (2 stars, last pushed yesterday), licensed MIT. It adds 111 tokens to every session and 1,927 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to descript, differing in 20 lines, and is treated as a copy.
Other skills, from other repositories
writing-skills
Use when creating new skills, editing existing skills, or verifying skills work before deployment.
receiving-code-review
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation.
writing-plans
Use when you have a spec or requirements for a multi-step task, before touching code.
skill-authoring
Author SKILL.md skills: frontmatter, validator limits, structure.
skill-creator
Create, improve, evaluate, benchmark skills. Use when authoring a new skill, updating an existing one, running evals, or optimizing a skill's description for triggering. Don't use for invoking skills, writing prose, or scaffolding Python projects.
iflytek-hyper-tts
A text-to-speech tool that turns written text into an MP3 recording. It can use an authorized voice and adjust speaking speed, volume, and pitch.