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call_chain

Trace callers and callees at a specific code line when the symbol name is unknown. Provide a file path and line number to map call relationships, with adjustable depth and result limits for targeted analysis.

Instructions

Callers/callees at a line; use when you know line, not symbol name. Symbol-level? impact_analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileYesFile path relative to workspace_dir (e.g. "src/auth.py")
lineNoLine number. OR symbol (at least one required).
depthNoCall chain depth (default: 2, max: 10)
symbolNoSymbol name. OR line. Both? symbol wins.
max_calleesNoMax callees to return (default: 20)
max_callersNoMax callers to return (default: 20)
workspace_dirYesREQUIRED: project root (abs). reindex first if new.

Schema Changelog

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

  1. First observed

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations provided, the description must carry the behavioral disclosure burden. It explains that the tool works at a line level and returns callers/callees, but does not detail return format, pagination, or any potential side effects. For a simple query tool, this is adequate but not rich.

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 extremely concise, using two short sentences with no fluff. It front-loads the core purpose and immediately provides usage context. Every word contributes to clarity.

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

Completeness4/5

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

Given the tool's moderate complexity (7 parameters, no output schema), the description is largely sufficient. It explains the core use case and points to a sibling for symbol-level queries. However, it omits any mention of return structure or behavior details like depth limits, which are in the schema but not described. Still, it is reasonably complete for a query tool.

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 coverage is 100%, so the baseline is 3. The description adds little to parameter understanding beyond what is already in the schema. The line/symbol relationship is already captured in the schema's anyOf and descriptions. No additional semantic meaning is provided.

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 the tool's function: 'Callers/callees at a line'. It specifies the resource (line) and the operation (retrieving callers and callees). It also distinguishes itself from the sibling tool impact_analysis by explicitly noting the line-based vs symbol-based use case.

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

Usage Guidelines5/5

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

The description provides explicit guidance: 'use when you know line, not symbol name' and direct the user to impact_analysis for symbol-level queries. This clearly indicates when to use this tool versus an alternative.

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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