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/telagod/code-abyss/analyzing-spreadsheetsnpx skills add telagod/code-abyss --skill analyzing-spreadsheetsgit clone --depth 1 https://github.com/telagod/code-abyssWhat 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 | $0.00074 | $0.00517 |
| Opus 5 | $0.00037 | $0.00259 |
| Sonnet 5 | $0.00015 | $0.00103 |
| Haiku 4.5 | $0.00007 | $0.00052 |
Grade A, and why
analyzing-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 2d 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.
What it actually says
XLSX Processing
Create, edit, analyze .xlsx files. LibreOffice required for formula recalculation via recalc.py.
Iron Rule
Zero formula errors at delivery. All formulas must compute — no #REF!, #DIV/0!, #VALUE!, #N/A, #NAME?. Always run recalc.py after writing formulas.
Decision Matrix
| Task | Tool | Reference |
|---|---|---|
| Data analysis, bulk ops, simple export | pandas | recipes.md |
| Formulas, formatting, Excel features | openpyxl | recipes.md |
| Financial model standards | — | financial-model.md |
| Recalculate formulas | recalc.py |
recipes.md |
Common Workflow
- Choose tool: pandas for data, openpyxl for formulas/formatting
- Create/Load workbook
- Modify data, formulas, formatting
- Save
- Recalculate (MANDATORY if formulas):
python recalc.py output.xlsx - Verify & fix errors — check JSON output, fix
#REF!/#DIV/0!/#VALUE!/#NAME?
Hard Constraints
- Use formulas, not hardcoded values — calculations stay dynamic. See recipes.md.
- Preserve existing templates — match existing format/style EXACTLY when updating; user template overrides defaults.
- Financial models — follow color/format conventions in financial-model.md.
Code Style
- Concise Python, no unnecessary comments or print statements.
- Excel files: comment cells with complex formulas, document hardcode sources.
What ships with it
3 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.
- 2d ago First seen · 45 lines · 74 tokens per session scan A 8696936d1974
analyzing-spreadsheets is a skill published in the GitHub repository telagod/code-abyss (240 stars, last pushed 1mo ago), licensed MIT. It adds 74 tokens to every session and 517 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 2026-08-30.
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