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List data sources

list_sources
Read-only

List the systems and files this workspace's scans read: where the data behind the map lives. Read it before you query a source system, to know which export holds what; pass system for one system's files in full. Per system: file export or connection, when a scan last read it, whether the current map was built from that scan, and per file its path, format, record count and the objects built from it. Metadata only: no row, no value; paths are the export's own names, and Maplith tries to mask personal data in them. asked holds what a person stated about a system (owner as a team, refresh cadence, retention, access, sensitivity, warehouse hints); unknown means nobody answered: never guess it, ask your human. A key limited to part of the map sees a file only when every object built from it is in its scope. work_done_here counts the work agents reported in each system. Files under the wrong system are re-homed with correct_source_system.

Input Schema

NameRequiredDescriptionDefault
systemNoOne system as list_sources names it, e.g. "economic". Omit for every system.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior5/5

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

Annotations only say readOnly/non-destructive/closed-world; the description adds substantive context beyond that: metadata-only with no row values, personal data masking in paths, permission scoping ("a key limited to part of the map sees a file only when every object built from it is in its scope"), and the meaning of unknown in asked data. This is exactly the non-obvious behavior an agent needs.

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?

Purpose is front-loaded, then the response shape, then the semantic caveats. Dense and largely earning its place, though the later clauses (asked/unknown, work_done_here, re-homing) run together in long semicolon chains and could be split for faster scanning.

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?

No output schema exists, and the description compensates by enumerating the returned fields per system and per file (export/connection, last scan, map provenance, path, format, record count, objects built from it) plus the asked/work_done_here attributes. Nothing an agent needs to call or interpret it is missing.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3; the description earns above that by clarifying the default (omit = every system) and that naming one system returns that system's files in full, which the schema only implies.

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?

Opens with a specific verb+resource ("List the systems and files this workspace's scans read") and immediately frames it as the inventory behind the map, which separates it from query-oriented siblings like search, fetch and get_value_summary. An agent can tell what this returns without opening the schema.

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?

Gives an explicit use case ("Read it before you query a source system, to know which export holds what") and a scoping instruction ("pass system for one system's files in full"). It also points to correct_source_system for the remediation case. It stops short of naming a clear when-not/alternative tool, so not a 5.

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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