Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add ZachArticulateV/designer-pro-and-seo/plugin install designer-pro-and-seoWrote 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/zacharticulatev/designer-pro-and-seo/csv-to-report)<a href="https://agentmods.dev/skills/zacharticulatev/designer-pro-and-seo/csv-to-report"><img src="https://agentmods.dev/badge/skills/zacharticulatev/designer-pro-and-seo/csv-to-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/zacharticulatev/designer-pro-and-seo/csv-to-report"><img src="https://agentmods.dev/badge/skills/zacharticulatev/designer-pro-and-seo/csv-to-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 | $0.00088 | $0.00683 |
| Opus 5 | $0.00044 | $0.00342 |
| Sonnet 5 | $0.00018 | $0.00137 |
| Haiku 4.5 | $0.00009 | $0.00068 |
Grade A, and why
csv-to-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 12d 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
csv-to-report
Family: content-and-data Status: Stable
Purpose
Turn raw CSV data into a structured, narrative report. A small Python helper does the deterministic profiling/filtering/grouping; the skill adds the human layer — what the columns mean and what the business rules are.
The 3-step framework: Load + label → Define rules → Request the structured deliverable, then iterate (same data, new lenses). Common uses: training compliance, staff scheduling, billing audits, inventory snapshots.
Triggers
- "csv to report" / "report from this csv"
- "summarize this spreadsheet"
- "training log report" / "compliance report"
- "turn this data into a report"
Inputs
- CSV file (path or pasted)
- Column meanings (labels the agent needs to interpret correctly)
- Business rules (what counts as overdue, complete, required, etc.)
- Desired deliverable format
Steps
- Profile the data mechanically:
Returns row/column counts, per-column type + fill rate + distinct values, numeric stats, and top categories — so labeling is grounded in real data.python3 "${CLAUDE_PLUGIN_ROOT}/scripts/workflow/csv_to_report.py" --in <file.csv> --human # use `py` on Windows if python3 is absent - Load + label. Confirm what each non-obvious column means (abbreviations, joined fields, date formats). Flag data-quality issues the profile reveals (blanks, mixed types, totals rows mixed into data rows).
- Define rules. Capture explicit business rules ("annual training expires 365 days after Completion_Date"; "overdue = past expiration AND status != complete").
- Slice as needed using the helper's
--filter,--group-by, and--selectflags to answer specific questions deterministically. - Render the deliverable — table, grouped lists, narrative summary, or an exported sub-CSV — applying the business rules to the profiled data.
- Offer an iteration menu — filter, group, export, re-summarize on the same data ("now only clinical staff", "now group by training type").
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.
- 12d ago First seen · 69 lines · 88 tokens per session scan A 01edbc544d51
csv-to-report is a skill published in the GitHub repository ZachArticulateV/designer-pro-and-seo (8 stars, last pushed 2mo ago), licensed MIT. It adds 88 tokens to every session and 683 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.
Other skills, from other repositories
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add-excel
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Brand-aware Excel engine. Use to (1) EXTRACT a company's brand from a .xlsx template into a reusable "Brand Profile", (2) COMPREHEND the template with the model (optional), (3) VERIFY it, (4) GENERATE a new on-brand .xlsx from a GridDocument fill manifest. Trigger on "extract our brand", "use our workbook template"…
analyze
Analyze a large file (CSV, Excel, PDF, JSON, code) and return a token-efficient summary. Instead of reading thousands of rows or pages, get schema + statistics + sample in under 500 tokens. Use when user mentions a file path, asks to analyze data, pastes many rows, or references a CSV/Excel/PDF/JSON file.
gsheets
Google Sheets via MCP — read, write, create, list, share spreadsheets. Use when reading, writing, or managing Google Sheets data.
visibly-seo-pdf-build
Build a clean, brand-compliant PDF from an analysis or offer. Use when the user asks to generate, render, or export a client-ready PDF presentation or document with their corporate identity — cover page, header/footer, section bars, tables, ROI boxes.