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senoff

xlsx-for-ai

xlsx_healer_diagnose

Read-onlyIdempotent

Diagnose broken external workbook references, missing defined names, #REF! errors, and credential-embedded Power Query connections in .xlsx files. Returns structured report for downstream repair.

Instructions

produce a structured diagnostic report of external references that are broken or at risk in a workbook. Returns five classes of finding: (1) external-workbook references that can't resolve, (2) defined-name external refs, (3) Power Query connections with embedded credentials, (4) #REF! propagation maps from upstream breakage, (5) multi-hop chains (workbook → workbook → workbook). Findings carry reference_id keys that downstream cure operations key on.

USE WHEN: a workbook shows #REF! errors, an agent moves a file and refs need rewriting, a customer reports "the workbook stopped working after we reorganized SharePoint", or auditing a corpus for hidden external-link breakage before sharing.

DO NOT USE WHEN: the user wants the cleaning/normalization surface (use xlsx_data_clean — different concern). Or when there is no .xlsx source path (Healer reads the source bytes, doesn't reconstruct from a structured spec).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_b64Yes
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare read-only and idempotent. Description adds detail on output structure (five finding classes with ref_id keys) and input requirement (source bytes, no reconstruction from spec). No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Efficiently structured: purpose statement, enumerated findings, usage guidance. No redundant text. Front-loaded with main action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Single parameter description implicitly clear. Covers purpose, output structure (five finding classes with reference_ids), usage scenarios, and exclusions. No missing needed context for agent to decide.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema lacks any description for file_b64. The description indirectly explains it's the source bytes of the .xlsx file, but doesn't specify encoding or constraints. Adds some value over schema but leaves gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clear verb+resource with enumerated finding types. Explicitly distinguishes from sibling xlsx_data_clean and indicates relationship to healer_cure. No ambiguity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit when to use with concrete examples, and when not to use with alternative tool named. No gaps.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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