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 agentmods add skills/paulrberg/agent-skills/spreadsheetsnpx skills add PaulRBerg/agent-skills --skill spreadsheetsgit clone --depth 1 https://github.com/PaulRBerg/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/paulrberg/agent-skills/spreadsheets)<a href="https://agentmods.dev/skills/paulrberg/agent-skills/spreadsheets"><img src="https://agentmods.dev/badge/skills/paulrberg/agent-skills/spreadsheets.svg" alt="Measured on agentmods" 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 | $0.00057 | $0.01272 |
| Opus 5 | $0.00028 | $0.00636 |
| Sonnet 5 | $0.00011 | $0.00254 |
| Haiku 4.5 | $0.00006 | $0.00127 |
Grade A, and why
spreadsheets 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 6d 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spreadsheets
Handle tabular data with exact values, minimal diffs, recipient-scoped data handling, atomic writes, and structural validation.
Invariants
- Keep precision-sensitive amounts as strings and compute with
decimal.Decimalor DuckDBDECIMAL(38, 18), never binary floats. - Touch only requested rows, columns, formulas, and formatting. Existing file conventions override house defaults.
- For newly authored text tables, prefer TSV, UTF-8 without BOM, LF, one trailing newline, lowercase
snake_caseheaders, ISO dates,.decimals, and-nulls. - Read unknown text tables with BOM-tolerant UTF-8; never write a BOM.
- Write in place atomically through a sibling temporary file, validate it, then replace the target.
- Escape external cells beginning with
=,+, or@; a bare-null is exempt. Formula-prefix cells in trusted authored data are observations, not proof of injection. - Treat transaction, bank, exchange, and tax data as user-owned. Use unredacted samples in internal agent reports when
materially useful; use
--redact-samplesfor public or third-party disclosures or when the user asks.
Factual Profiling
Resolve helper paths from this SKILL.md. Profile unknown data before choosing a transformation tool:
uv run "<skill-dir>/scripts/profile.py" <file>
The JSON output has schema_version: 2. It reports structural facts, header quality, cardinality/statistics when qsv is
available, frequency facts, formula-prefix cells, workbook metadata, and local tool availability. It contains no tool
recommendations and does not infer identifiers from uniqueness. Choose the tool from the requested transformation,
provenance, output format, and preservation requirements.
Use --external-data only when the cells came from an external or otherwise untrusted source and will be written to a
formula-capable consumer. With that flag, formula-prefix cells affect status; without it, legitimate formulas such as
=SUM(...) remain factual observations and do not fail the profile.
What ships with it
7 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.
- 6d ago First seen · 96 lines · 57 tokens per session scan A 62f01484436b
spreadsheets is a skill published in the GitHub repository PaulRBerg/agent-skills (70 stars, last pushed yesterday), licensed MIT. It adds 57 tokens to every session and 1,272 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 2026-08-30.
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