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nietsneuah

filemaker-mcp

by nietsneuah

fm_delete_context

Remove outdated context entries for FileMaker tables or fields, such as when a field is renamed or a hint is no longer accurate.

Instructions

Delete an operational learning about a FileMaker field or table.

Call this to remove stale or incorrect context entries — for example, when a table or field has been renamed/deleted, or when a previously saved hint is no longer accurate.

The record is deleted from FM and removed from the local cache immediately.

Args: table_name: Table this applies to (e.g., "Invoices"). field_name: Specific field name, or empty for table-level context. context_type: Category — "field_values", "syntax_rule", "query_pattern", "relationship".

Returns: Confirmation message or error description.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
field_nameNo
table_nameYes
context_typeNofield_values

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations exist, so the description carries full burden. It discloses that the record is deleted from FM and removed from local cache immediately. It does not mention authorization or potential side effects, but for a delete operation this is adequate.

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

Conciseness4/5

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

The description is clear and well-structured, with separate paragraphs for purpose, usage, and parameters. However, the Args section could be streamlined into a more concise format without losing clarity.

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?

Given the tool's complexity (3 parameters, no annotations, output schema exists), the description covers all aspects: what it does, when to use, the effect (immediate deletion), and return type (confirmation/error). It is complete for an AI agent to select and invoke correctly.

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

Parameters5/5

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

Schema description coverage is 0%, yet the description explains each parameter with examples: table_name (e.g., 'Invoices'), field_name (empty for table-level), context_type (lists categories like field_values, syntax_rule). This adds significant meaning beyond the schema, which only has defaults and types.

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?

The description clearly states it deletes an operational learning context entry for a FileMaker field or table. The verb 'delete' and resource are specific, and it is easily distinguished from siblings like fm_save_context (which saves) and query tools.

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

Usage Guidelines4/5

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

The description specifies when to use: removing stale or incorrect context entries, with concrete examples (renamed/deleted fields, inaccurate hints). It implies when not to use (when context is accurate) but lacks explicit when-not or alternative tools.

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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