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 richfrem/agent-plugins-skills --skill os-improvement-reportgit clone --depth 1 https://github.com/richfrem/agent-plugins-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/richfrem/agent-plugins-skills/os-improvement-report)<a href="https://agentmods.dev/skills/richfrem/agent-plugins-skills/os-improvement-report"><img src="https://agentmods.dev/badge/skills/richfrem/agent-plugins-skills/os-improvement-report/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/richfrem/agent-plugins-skills/os-improvement-report"><img src="https://agentmods.dev/badge/skills/richfrem/agent-plugins-skills/os-improvement-report.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 | $0.00081 | $0.00919 |
| Opus 5 | $0.00041 | $0.00460 |
| Sonnet 5 | $0.00016 | $0.00184 |
| Haiku 4.5 | $0.00008 | $0.00092 |
Grade A, and why
os-improvement-report 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 yesterday.
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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Loop Progress Report
Visual and text reporting on the agentic loop improvement cycle — across any plugin that
maintains an improvement-ledger.md and results.tsv per skill.
The reference output is the autoresearch progress chart: green KEEP dots on a timeline, gray DISCARD dots, running-best step line, annotations showing what each improvement was. This skill produces the same chart for agentic-os and exploration-cycle-plugin improvement cycles.
Dependencies (Python 3.8+, pandas, matplotlib) are in references/detailed-reference.md.
What It Reads
| Source | Priority | Content |
|---|---|---|
context/experiment-log/index.md |
Primary | All logged runs; filter result_type: numeric for KEEP/DISCARD/score data from orchestrator runs |
context/memory/improvement-ledger.md |
Legacy fallback | Eval score progression written by os-improvement-loop Stage 4.7; used if experiment log has no numeric entries |
.agents/skills/*/evals/results.tsv |
Supplement | Per-skill detailed eval score history |
The experiment log is the unified source of truth for numeric results. The improvement ledger is a legacy format maintained for backward compatibility with older loop runs.
What It Produces
| Output | Description |
|---|---|
context/memory/reports/progress_YYYYMMDD_HHMM.png |
Progress chart: KEEP/DISCARD timeline, running-best step line, change annotations |
context/memory/reports/summary_YYYYMMDD_HHMM.md |
Text summary: baseline vs best, top hits by delta, survey effectiveness, north star trend |
Execution Flow
- Read experiment log for numeric entries — run
experiment_log.py summary, filtercontext/experiment-log/index.mdforResult Type: numericrows, and parse each linked file's KEEP/DISCARD verdict string. Fall through to Phase 1 if no numeric entries exist. Full parsing detail inreferences/detailed-reference.md. - Check legacy data availability (fallback only) — if
context/memory/improvement-ledger.mdis missing or its Section 1 table is empty, tell the user no cycles have completed yet rather than running the report on an empty ledger. - Run the report — invoke
generate_report.py --project-dir ... --plugin-dir ...(optionally--skill <name>). Exits 0 and prints the chart path + text summary. - Surface the output — report the chart path, print the text summary inline, and ask whether to open the chart image or show per-skill detail.
- Cross-plugin reporting (optional) — if tracking both
agent-agentic-osandexploration-cycle-plugin, run the report once per plugin's project dir and concatenate the text summaries. Full commands inreferences/detailed-reference.md.
What ships with it
17 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.
- evals/evals.json 1.6 KB
- evals/results.tsv 60 B
- improvement-ledger-spec.md 50 B
- post_run_survey.md 42 B
- references/acceptance-criteria.md 42 B
- references/chart-reading-guide.md 42 B
- references/detailed-reference.md 63 B
- references/fallback-tree.md 58 B
- references/memory/improvement-ledger-spec.md 56 B
- references/memory/post_run_survey.md 48 B
- references/operations/chart-reading-guide.md 56 B
- references/testing/test-scenarios-seed.md 53 B
- requirements.in 76 B
- requirements.txt 1.1 KB
- scripts/analysis.ipynb 31 B
- scripts/generate_report.py 35 B runs code
- test-scenarios-seed.md 47 B
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.
- yesterday Changed · -130 lines 43244c485baa
- 9d ago First seen · 198 lines · 81 tokens per session scan A 95302c77d32c
os-improvement-report is a skill published in the GitHub repository richfrem/agent-plugins-skills (6 stars, last pushed today), licensed MIT. It adds 81 tokens to every session and 919 once invoked, about $0.0004 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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