Skip to main content
Glama

ipt_configure_source

Set source parsing options (delimiter, quote, header lines, encoding, date format) and re-analyze the source. For SQL sources, provide raw connection fields.

Instructions

[writes to the IPT] Set how a source is parsed (delimiter, quote character, header lines, encoding, date format) and re-analyse it; for SQL sources pass raw fields (host, database, credentials, SQL).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNo
sourceYes
analyzeNo
encodingNo
delimiterNoe.g. \t or ,
shortnameYesResource shortname
dateFormatNo
enclosedByNo
headerLinesNo
multiValueDelimiterNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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

The description explicitly flags that the tool writes to the IPT and triggers re-analysis, which is useful behavioral context. However, with no annotations at all, it leaves details like whether existing analysis is overwritten, required permissions, and response behavior unstated.

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 a single dense sentence that front-loads the write side effect, states the core action and relevant fields, then adds the important SQL-source branch. No wasted words, though the density makes it slightly harder to parse.

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

Completeness2/5

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

Given 10 parameters, 20% schema coverage, no annotations, and no output schema, the description is too brief to fully prepare an agent to call the tool correctly. It omits parameter-level details, return behavior, and side effects on existing parsed data.

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 description coverage is only 20%, so the description must compensate; it successfully maps several prose terms to parameters (delimiter, quote character -> enclosedBy, header lines, encoding, dateFormat) and explains the `fields` parameter for SQL sources. Still, it leaves shortname, source, analyze, and multiValueDelimiter largely unexplained.

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

Purpose4/5

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

The description clearly identifies a specific action and resource: configuring how an existing source is parsed, with concrete attributes (delimiter, quote character, header lines, encoding, date format). It distinguishes itself from source-creation or validation tools, though it does not explicitly name any sibling.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives like ipt_add_source, ipt_peek_source, or ipt_validate_resource. The only usage hint is the SQL-specific branch ('for SQL sources pass raw fields'), which is useful but does not establish the broader selection criteria.

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