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lookup_symbol

Resolve a FLOX symbol across any binding to get its local name, kind, signature, and gotchas. Use when the user names a symbol and you need the correct cross-language spelling.

Instructions

Resolve a FLOX symbol across every surface (C++, C-API, Python, Node, Codon, QuickJS). Methods resolve too, reported as Owner.method. Returns the local name, kind, and signature for each binding that exports it. Use this whenever the user names a struct, function, or indicator and you need to know what it's called in their language — never guess at the cross-language spelling. Accepts any spelling the user knows ('FloxBarData', 'BarData', 'flox_indicator_ema', 'ema', 'Ema'). Filter to one language with the language arg if the user is writing in a specific binding. When the symbol has hand-curated semantic gotchas (silent quantization, ordering preconditions, subscribed-vs-registry distinctions), they appear under a ## Gotchas section in the response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesSymbol name in any binding's spelling. Case-sensitive; common transformations (Flox prefix, flox_indicator_ prefix) are tried automatically.
languageNoOptional binding filter. One of: capi, cpp, capi, python, node, codon, quickjs.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv0.6.9
  2. Removedv0.6.8
  3. First observedv0.6.3

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations provided, the description fully carries the transparency burden. It discloses return structure, handling of methods as Owner.method, acceptance of arbitrary spellings, and the presence of a '## Gotchas' section for semantic pitfalls. This gives the agent a solid understanding of what to expect.

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?

The description is well-structured and front-loaded with the core purpose, then return, usage, matching behavior, and gotchas. Every sentence adds distinct value with no redundancy or filler. It is concise yet comprehensive.

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 lack of an output schema, the description explains return fields (local name, kind, signature), input flexibility, and special notes (gotchas). For a cross-language lookup tool, this covers all necessary aspects an agent would need to select and invoke it correctly, and to interpret the result.

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?

The schema already covers both parameters with descriptions (100% coverage), so baseline is 3. The description adds meaningful extras: case-sensitivity, automatic spelling transformations, examples, and guidance on when to use the language filter. This enriches the semantic meaning beyond the schema, earning a 4.

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 states a clear, specific action: 'Resolve a FLOX symbol across every surface' and details the return value (local name, kind, signature). It clearly distinguishes from sibling tools like lookup_error_code or list_capi_functions by focusing on cross-language symbol resolution.

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?

It gives explicit when-to-use guidance: 'Use this whenever the user names a struct, function, or indicator... never guess at the cross-language spelling.' It also explains when to use the language filter. However, it does not explicitly name alternative tools or state when not to use it, stopping just short of a perfect score.

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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