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Glama

get_context_pack

Read-onlyIdempotent

Assemble a token-bounded bundle for one entity, several entities, or a plain-language question, with focal code and dependency routes, replacing multiple source and traversal reads.

Instructions

Assemble a token-bounded bundle from one entity, several entities, or a plain-language question: focal bodies plus dependency signatures and connecting routes. Call it instead of several get_entity_source and traversal reads.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNoDependency traversal depth
entitiesNoSeveral focal entity names or UUIDs when the question is about how they connect.
questionNoA plain-language question resolved to one or more focal entities before packing.
entity_idNoFocal entity UUID
max_charsNoSerialized characters this response may occupy; what was cut is named in `elisions`.
token_budgetNoToken budget (8000, 16000, or 32000)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.7.16

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive/closed-world, so the safety profile is covered. The description adds substantive behavior beyond that: the output is a token-bounded bundle containing focal bodies, dependency signatures, and connecting routes, which tells the agent this is a lossy, budget-constrained aggregation rather than an exhaustive dump.

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?

Two sentences, zero filler, and the primary capability is front-loaded ahead of the routing advice. Every clause carries information about what is produced or when to call it.

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?

With no output schema, the description usefully covers return composition and truncation behavior ('token-bounded'), and it explains the alternative it supersedes. Minor gaps remain around how the budget interacts with the two overlapping budget parameters, though that detail lives in the schema.

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 100%, including the anyOf branching requirement and per-field docs for depth, entities, question, entity_id, max_chars, and token_budget. The description restates the three input modes in prose but adds no format, default, or constraint detail beyond the schema, so the baseline of 3 applies.

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?

States a specific verb ('Assemble') and a specific artifact ('token-bounded bundle'), and enumerates the three input modes (one entity, several entities, a plain-language question). It also names the sibling it replaces (get_entity_source plus traversal reads), so an agent can route 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?

Explicitly says 'Call it instead of several get_entity_source and traversal reads', giving both a trigger (multiple related reads) and named alternatives. It lacks an explicit exclusion (e.g. when a single direct read is preferable), so it stops short of the full when/when-not bar.

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