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 distsystem/codex-desktop-linux --skill record-and-replaygit clone --depth 1 https://github.com/distsystem/codex-desktop-linuxWrote 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/distsystem/codex-desktop-linux/record-and-replay)<a href="https://agentmods.dev/skills/distsystem/codex-desktop-linux/record-and-replay"><img src="https://agentmods.dev/badge/skills/distsystem/codex-desktop-linux/record-and-replay/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/distsystem/codex-desktop-linux/record-and-replay"><img src="https://agentmods.dev/badge/skills/distsystem/codex-desktop-linux/record-and-replay.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 | $0.00038 | $0.00942 |
| Opus 5.5 | $0.00015 | $0.00377 |
| Sonnet 5.5 | $0.00008 | $0.00188 |
| Haiku 4.5 | $0.00004 | $0.00094 |
Grade A, and why
record-and-replay 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 1mo 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
100% identical to record-and-replay — 0 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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Record & Replay
Record the user's Linux workflow, inspect the event stream, and turn the repeatable intent into a reusable Codex skill. This is the same bundled Record & Replay product shell backed by a Linux-native event-stream server, not a raw pointer or keyboard macro recorder.
The bundled plugin launches ./bin/SkyLinuxComputerUseClient event-stream mcp.
That helper is the Linux equivalent of the macOS Sky Computer Use event-stream
client, implemented by the Rust codex-record-replay-linux backend.
Flow
- Call
doctorwhen readiness is uncertain. If Computer Use cannot observe the desktop, explain the blocker and offer the diagnostics/setup path before recording. - Call
skysight_startwhen recent activity context should keep accumulating before or during the demo, orskysight_snapshotwhen you only need a point-in-time local activity summary. Useskysight_pauseandskysight_resumeto stop or continue Chronicle-compatible resources without losing the active session, and useskysight_statusto find the resource paths and local OCR availability. Respectskysight_list_exclusionsand update exclusions before recording sensitive apps or domains. Treat OCR as local screen evidence metadata; do not copy raw OCR text into durable skill drafts unless it is necessary for the reusable workflow and safe to retain. - Call
event_stream_startwith a shortgoalwhen matching the upstream Record & Replay flow, orstartwhen you need Linux-specific options. The Linux app should show the active Record & Replay recording HUD while the shared runtime status is active. Native Linux audio evidence is opt-in and requires bothinclude_audio: trueand an affirmativeCODEX_RECORD_REPLAY_AUDIOsetting; normal workflow recording should rely on transcriptspeech_contextinstead. Tell the user that recording is active, that they should perform the workflow normally, and that they can saydonewhen finished. - During the demonstration, call
desktop_snapshotat meaningful app/window changes, such as after the user opens Chrome or arrives on a target site. Callmarkonly for meaningful intent boundaries that will help the future skill, such as "source page opened" or "finished selecting rows". - When transcript text is explicitly available during the recording, call
speech_contextwith the transcript. Treat the speech as user intent/context, not as audio to replay or Chronicle-compatible resources. Do not hijack the composer dictation UI as the recording architecture. - For browser workflows, call
browser_tracewhen browser/CDP trace evidence is available. Treat the trace as semantic evidence for drafting the skill, not as a click/coordinate replay script. - Use
event_stream_statusorstatusif you need to confirm which bundle is active. When the user says they are done, asks to stop, or the HUD sends "I'm done recording.", callevent_stream_stoporstopif the bundle is still active. - If the user discards the recording or the HUD cancel control is used, call
event_stream_cancelorcancelwithdiscarded: trueand treat the bundle as canceled evidence only. - Call
validate_bundle, thendraft_skill_prompt. - Use the draft prompt and the bundle evidence to create or update a normal
SKILL.md. Prefer stable app names, URLs, semantic UI labels, and data shape descriptions over literal coordinates. - Call
inspect_skillbefore import. Callimport_skillonly after the user approves the generated skill.
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.
- 1mo ago First seen · 75 lines · 38 tokens per session scan A 40c1c8091090
record-and-replay is a skill published in the GitHub repository distsystem/codex-desktop-linux (15 stars, last pushed 3mo ago), licensed MIT. It adds 38 tokens to every session and 942 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to record-and-replay, differing in 0 lines, and is treated as a copy.
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