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 dayfinggg/openai-codex-agent-skills --skill journalgit clone --depth 1 https://github.com/dayfinggg/openai-codex-agent-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/dayfinggg/openai-codex-agent-skills/journal)<a href="https://agentmods.dev/skills/dayfinggg/openai-codex-agent-skills/journal"><img src="https://agentmods.dev/badge/skills/dayfinggg/openai-codex-agent-skills/journal/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/dayfinggg/openai-codex-agent-skills/journal"><img src="https://agentmods.dev/badge/skills/dayfinggg/openai-codex-agent-skills/journal.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 | $0.00050 | $0.00446 |
| Opus 5 | $0.00025 | $0.00223 |
| Sonnet 5 | $0.00010 | $0.00089 |
| Haiku 4.5 | $0.00005 | $0.00045 |
Grade A, and why
journal 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 3d 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 — 35 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Journal
Follow the governing instructions and the user's requirements for communication, code style, authorization, and delegation. This skill supplies task-specific guidance, not permission to expand the task. Its workflow and output fields describe internal checks and relevant content, not a mandatory response layout or a progress report. When used within broader authorized work, continue that work through completion rather than stopping to deliver this skill's intermediate result.
Record decisions that affect trust in the result, not a transcript of activity.
Decide what deserves a record
Log a choice when alternatives existed, a hypothesis changed the investigation, a risk was accepted, a user constraint redirected work, or evidence changed the plan. Skip routine reads, commands, and obvious mechanical edits.
Also log a material change to an estimate, commitment, scope, dependency owner, escalation threshold, or fallback when later reviewers would otherwise misread what was promised and why it changed.
Record the decision
Each entry must include time or sequence, decision, reason, evidence, affected scope, result, and status. Link stable artifacts or commands instead of pasting large outputs. Mark superseded entries without deleting their history.
When the entry changes a commitment, identify the stakeholder decision, the previous and revised forecast or scope, and the evidence that triggered the change.
Keep it reviewable
Use one row or compact block per decision. Keep facts separate from inference. Do not store secrets, personal data, credentials, or unredacted production content.
Boundaries
Maintain a journal only when requested or when an existing authorized workflow requires a durable decision record. Otherwise keep working context internal. Use the specified destination, omit secrets, and do not commit, publish, or send the journal without user authorization. A journal supports verification but does not replace it.
Output
Update the authorized decision record without progress narration. Return the record when requested, otherwise include only its relevant result in the final response. Do not append unsolicited recommendations.
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.
- 3d ago Changed · +2 lines aa82b691b2db
- 4d ago Changed · +4 lines 7ad94bf578c1
- 10d ago First seen · 29 lines · 50 tokens per session scan A 8ef785ce6451
journal is a skill published in the GitHub repository dayfinggg/openai-codex-agent-skills (4 stars, last pushed today), licensed MIT. It adds 50 tokens to every session and 446 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 2026-08-31.
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Systematic review response workflow from comment analysis to professional rebuttal writing. Use when the user asks to "write rebuttal", "respond to reviewers", "draft review response", or "analyze review comments". Improves paper acceptance rates.
daily-paper-generator
Use when the user asks to generate daily paper digests on a general topic. This skill supports both arXiv and bioRxiv (or either one), then produces structured Chinese/English summaries for selected papers.