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 nimabahrami/pypsa-skills-kit --skill pypsa-reportinggit clone --depth 1 https://github.com/nimabahrami/pypsa-skills-kitWrote 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/nimabahrami/pypsa-skills-kit/pypsa-reporting)<a href="https://agentmods.dev/skills/nimabahrami/pypsa-skills-kit/pypsa-reporting"><img src="https://agentmods.dev/badge/skills/nimabahrami/pypsa-skills-kit/pypsa-reporting/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/nimabahrami/pypsa-skills-kit/pypsa-reporting"><img src="https://agentmods.dev/badge/skills/nimabahrami/pypsa-skills-kit/pypsa-reporting.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 | $0.00114 | $0.00744 |
| Opus 5 | $0.00057 | $0.00372 |
| Sonnet 5 | $0.00023 | $0.00149 |
| Haiku 4.5 | $0.00011 | $0.00074 |
Grade A, and why
pypsa-reporting 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 11d 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 — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PyPSA Reporting
Charts = instruments, not decoration: every catalog figure doubles as a bug detector. Boundary: numeric interpretation + sanity battery = pypsa-solve-and-debug | plausibility judgment = pypsa-physical-realism | this skill RENDERS.
Two layers, always this order:
- diagnostic layer = compact panel (energy balance | prices | SOC | shedding) FIRST on every solved network. Diagnostics wrong -> STOP, fix model before presentation figures.
- presentation layer = deliverable figures matching study question.
Adapt, don't impose
- DETECT user's plotting stack from their code (matplotlib default | plotly/altair/web -> carry palette + restraint, not the API).
- scripts/standard_plots.py = runnable generator AND copy-from pattern library — lift single functions into user's own reporting flow.
- project palettes/configs OVERRIDE bundled palette.
Workflow
- READ references/design-system.md before any figure (palette | typography | layout | data-ink rules).
- PICK figures from references/chart-catalog.md — each entry: PURPOSE | BUILD | CATCHES.
- Canonical set in one shot:
python scripts/standard_plots.py solved_network.nc --outdir figures(imports scripts/plot_style.py | optional assets/pypsa-report.mplstyle). - anything suspicious -> references/diagnostics.md = symptom -> chart -> root cause -> owning skill.
Non-negotiable conventions
- carrier colors CONSISTENT across every figure of a report. plot_style.py owns mapping | user config overrides | never ad hoc per figure.
- diagnostic panel ships w/ EVERY report, even single-figure asks.
- remaining hard rules (takeaway titles | units on axes | caveat captions | binding-event annotation — ! clean chart of a constrained system = lie of omission) = references/design-system.md, loaded by workflow step 1.
- caption caveat wording: run type | weather year | foresight -> pypsa-solve-and-debug/references/interpreting-results.md Reporting discipline | market caveats -> pypsa-market-design | revenue caveats -> pypsa-asset-economics.
What ships with it
6 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.
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.
- 11d ago First seen · 44 lines · 0 tokens per session scan A b232de9ba52b
pypsa-reporting is a skill published in the GitHub repository nimabahrami/pypsa-skills-kit (23 stars, last pushed 2mo ago), licensed MIT. It adds 114 tokens to every session and 744 once invoked, about $0.0006 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.
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