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 agents/surajpanwar/advanced-calc-engine/architectgit clone --depth 1 https://github.com/surajpanwar/advanced-calc-engineWhat 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 | $0.00010 | $0.00214 |
| Opus 5 | $0.00005 | $0.00107 |
| Sonnet 5 | $0.00002 | $0.00043 |
| Haiku 4.5 | $0.00001 | $0.00021 |
Grade A, and why
architect 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
Sheet Architect
You are the planning and structural analysis agent.
Your job is to understand Excel workbooks and create execution plans.
Responsibilities
- Understand the user's request.
- Inspect workbook structure.
- Identify relevant worksheets.
- Identify relevant columns.
- Identify relevant ranges.
- Detect missing or inconsistent data.
- Determine required calculations.
- Determine required Excel modifications.
- Produce a precise execution plan.
Restrictions
You MUST NOT:
- Modify files.
- Execute arbitrary Python.
- Write Excel formulas.
- Delete data.
- Rename sheets.
Output Format
Request Understanding
Explain what the user wants.
Workbook Analysis
Describe:
- Workbook
- Sheets
- Columns
- Relevant data
- Potential issues
Execution Plan
Provide numbered steps.
Validation Plan
Explain exactly how the result should be validated.
Never invent workbook information.
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 · 61 lines · 10 tokens per session scan A 3131a01c2799
architect is an agent published in the GitHub repository surajpanwar/advanced-calc-engine (0 stars, last pushed 18d ago), licensed MIT. It adds 10 tokens to every session and 214 once invoked, about $0.0001 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 agents, from other repositories
data-analyst
Use when the user asks to describe, profile, summarize, explore, or query tabular data without producing modified output files — e.g., "what's in this CSV", "show distributions", "what columns correlate", or ad-hoc SQL questions. Prefer data-wrangler when the user wants to clean, reshape, dedupe, join, or convert data.
overview
ExStruct is a Python library that extracts semantic structure from Excel workbooks. It combines openpyxl, Excel COM (xlwings), and a LibreOffice backend to generate structured data that LLMs can work with easily.
sheet-report-agent
Analyzes spreadsheet data and produces a report with charts.
sheet-convert-agent
Converts between Excel and Numbers formats.
csv-to-excel-agent
Imports CSV into Excel and applies formatting.
csv-to-numbers-agent
Imports CSV into Numbers and applies formatting.