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 exon-research/genomi --skill journalgit clone --depth 1 https://github.com/exon-research/genomiWrote 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/exon-research/genomi/journal)<a href="https://agentmods.dev/skills/exon-research/genomi/journal"><img src="https://agentmods.dev/badge/skills/exon-research/genomi/journal.svg" alt="Measured on agentmods" 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 | $0.00027 | $0.00950 |
| Opus 5 | $0.00014 | $0.00475 |
| Sonnet 5 | $0.00005 | $0.00190 |
| Haiku 4.5 | $0.00003 | $0.00095 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Journal and Research Memory
Use journal when an investigation spans multiple Genomi tools and the host agent needs to record reasoning, evidence links, or reviewed source findings.
Goal
Record the host agent's observations, hypotheses, decisions, contradictions, plans, summaries, and unresolved questions while preserving traceability to Genomi operations and evidence identifiers.
Journal entries are the append-only notebook. Reviewed research records are source-memory entries in the evidence DB. They live in the same capability because both preserve investigation memory, but they have different roles: journal entries explain what the host agent concluded or still needs to check; reviewed research records store source-backed findings for reuse.
Neither journal entries nor reviewed research records rank candidates by themselves. Candidate ranking still belongs to the relevant evidence tools, with reviewed source records passed only when a tool explicitly accepts them.
Scopes
session: current chat/session notebook. It may link private/sample evidence only after scoped Active Genome Index access is approved for this session.project: current workspace notebook. It is public/target-scoped and rejects private/sample evidence links.
Cross-Capability Synthesis
A scope-limited result from this capability is not a final user-facing answer when other Genomi capabilities can contribute orthogonal evidence to the same question. Returning "cannot answer" while applicable capabilities remain unexamined is a host-agent failure mode.
Tools
journal.append_entry
Append a new journal entry, or append evidence links and/or an amendment to an existing entry.
Use when: Record an observation, hypothesis, decision, contradiction, plan, summary, unresolved question, or append evidence/amendment to an existing entry.
Why necessary: Multi-tool investigations need one append-only write path for notes, evidence links, and corrections so agents do not sequence separate journal mutations.
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 · 113 lines · 27 tokens per session scan A ec74a7c8e2cf
journal is a skill published in the GitHub repository exon-research/genomi (481 stars, last pushed 7d ago), licensed Apache-2.0. It adds 27 tokens to every session and 950 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
context-engineering
Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.
claude-compaction-restore
Use when a Claude Code session has just compacted, is about to compact, reached context limit, resumed after /compact, or needs to rebuild its working mental model from Claude JSONL transcripts and touched files.
agentic-os
A design for running persistent specialist agents, commands, scripts, and file-based memory inside Codex. It keeps the setup in project files so it can continue across sessions.
memory-and-handoff
Two-mode skill: (1) session memory — load/persist durable workflow state under .cc10x/ (activeContext, patterns, progress) so context survives compaction; (2) handoff package — portable, secrets-redacted export for a coworker, different tool, or fresh non-cc10x session.
agent-common
Shared preamble loaded by all cc10x agents — memory protocol, contract format, output rules.
context-engineering
Use when designing, reviewing, or debugging how an agent's context window gets filled, pruned, or shared — choosing what loads at boot versus on demand, sizing an install or an always-loaded file, fixing an agent that drifts, repeats itself, or forgets constraints mid-task, planning compaction or summarization…