Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add glebis/claude-skills/plugin install recordingWrote 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/glebis/claude-skills/recording)<a href="https://agentmods.dev/skills/glebis/claude-skills/recording"><img src="https://agentmods.dev/badge/skills/glebis/claude-skills/recording/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/glebis/claude-skills/recording"><img src="https://agentmods.dev/badge/skills/glebis/claude-skills/recording.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 | $0.00057 | $0.01207 |
| Opus 5 | $0.00028 | $0.00603 |
| Sonnet 5 | $0.00011 | $0.00241 |
| Haiku 4.5 | $0.00006 | $0.00121 |
Grade A, and why
recording 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 6d 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Recording Mode
Activate this mode when the user runs /recording or otherwise signals a demo/screen-share. Stay in this mode for the rest of the session unless the user says "stop recording", "/recording off", or equivalent.
Core rule
While recording mode is active, every user-visible output (chat text, code, file contents shown inline, tool result summaries, commit messages, file names invented for examples) MUST have sensitive content replaced with obviously fake placeholder data before it leaves the assistant.
This applies to text the model generates. It does NOT retroactively edit files on disk — only what the audience sees on screen. If asked to write redacted content to a file, do so explicitly; otherwise leave files alone.
What to redact
Replace these categories:
- Names (people, partners, family, colleagues, clients) →
Alex Doe,Jamie Roe,Sam Park - Handles / emails / phones / URLs with identifiers →
@demo_user,[email protected],+49 000 000 0000 - Org / company / brand names (when private) →
Acme Co,Globex - Locations — anything more specific than continent. City, neighborhood, street, venue, coordinates, IP-derived location →
Some City,Main Street,Venue A. Even "Berlin" gets replaced if it could identify the user. - Dates — any real calendar date (birthdays, appointments, sessions, deadlines, deploy dates, transaction dates, file timestamps shown inline) → shift to placeholder dates like
2025-01-01,2025-01-02. Keep relative ordering and weekday if it matters to the demo. Today's actual date should be replaced too if it appears in output. - Financial values (revenue, prices, salaries, invoice amounts) → round dummy numbers like
€1,234or$X,XXX - Medical info (diagnoses, medications, doses, symptoms, lab values) →
[medication],[condition],[symptom] - Emotional / therapy / coaching content (feelings, session notes, DIMs/SIMs, relationship details) →
[personal reflection] - Business info (deal terms, client lists, internal strategy, unreleased projects) →
[business detail] - Credentials (tokens, keys, passwords, session IDs, file paths containing usernames) →
sk-XXXX,/Users/demo/... - Genetic / health data specific to the user →
[genetic marker]
What ships with it
1 file 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.
- 6d ago First seen · 73 lines · 57 tokens per session scan A c9fce7e2f795
recording is a skill published in the GitHub repository glebis/claude-skills (374 stars, last pushed 8d ago), licensed MIT. It adds 57 tokens to every session and 1,207 once invoked, about $0.0003 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.
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