Skip to main content
Glama

Fetch programming manual

fetch_manual

Download an instrument's user or programming guide into a local index so AI can reference model-specific SCPI commands and settings.

Instructions

Download this model's user/programming guide into the local brain and index it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoPDF/HTML URL or local file path. If omitted, web-search the model.
resourceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
deepNo
modelNo
notesNo
cachedNo
dialectYes
optionsNo
identityYes
resourceYes
help_headsNo
manual_urlNo
rememberedNo
manual_pathNo
profile_keyNo
cookbook_uriYes
manual_charsNo
manufacturerNo
knowledge_dirNo
instrument_classNo
starter_commandsYes
recommended_toolsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses that the manual is downloaded into a local brain and indexed, but does not mention permissions needed, network access, whether existing indexed content is overwritten, failure behavior, or other side effects.

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 front-loaded sentence with no wasted words. It is concise, though its brevity leaves important behavioral and parameter details unaddressed elsewhere.

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?

Although an output schema exists, the description is incomplete for a tool with no annotations and a partially documented schema. It does not explain the resource parameter, prerequisites, storage implications, or when an agent should prefer this tool over siblings such as learn_instrument.

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

Parameters2/5

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

Schema coverage is 50%. The url parameter is well described in the schema itself, but the resource parameter has no schema description and is not explained in the tool description. The description adds no parameter meaning beyond what is already in the structured schema.

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 states a specific verb+resource: downloading this model's user/programming guide and indexing it locally. It clearly differs from many sibling tools like open_instrument or scope_capture_waveform, but it does not explicitly differentiate itself from learn_instrument or search_scope_knowledge.

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 explicit guidance on when to use this tool versus alternatives, nor any listed prerequisites or exclusions. The only implied usage is that an agent should call it to obtain a model manual, but nothing states when that is appropriate.

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