Skip to main content
Glama

agda_retrieve_goals

Retrieve current visible goals and opaque handles from an Agda workspace to support interactive proof editing and goal inspection.

Instructions

Retrieve the current visible goals and opaque handles

Input Schema

NameRequiredDescriptionDefault
asyncNotrue always returns a job handle; false blocks until Agda finishes
timeoutMsNoOverride the configured Agda command timeout for this call
workspaceYesOpaque workspace handle returned by agda_load_module
includeRawNoInclude Agda's native event log; omitted by default because it is large
deferAfterMsNoHow long this call may block before returning a job handle; capped by maxJobWaitMs

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.3.1
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observedv0.3.0

TDQS

C2.5/5.0
Behavior2/5

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

No annotations are provided, so the description bears the full disclosure burden. It says nothing about the tool's asynchronous nature, its blocking behavior, or that it can return a job handle instead of goals (flags that exist in the schema as async/deferAfterMs). For a tool in a job-handle-based workflow, that omission forces the agent to infer behavior from parameter names alone.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One short sentence with no filler and the object front-loaded, so nothing is wasted. But at eight words it crosses from concise into under-specified, and "opaque handles" adds ambiguity rather than information.

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?

This is a five-parameter tool with async/job-handle semantics, no annotations, and no output schema. The description does not explain what a "handle" is, that results may be deferred into a job, or what the returned goals look like — leaving the agent to reconstruct the interaction model from parameter names.

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%, with every parameter documented in-schema (workspace handle provenance, async semantics, timeout override, includeRaw size caveat). The description adds nothing 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.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a verb ("Retrieve") and an object ("current visible goals and opaque handles"), so the intent is roughly graspable. However, "opaque handles" is undefined jargon and there is no differentiation from closely related siblings such as agda_query_metavariables, agda_retrieve_constraints, or agda_retrieve_context. An agent cannot tell from this sentence which of those four it should call.

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 when-to-use guidance, no prerequisite (e.g., a loaded module), and no mention of alternatives. The only cue is implicit in "current visible goals", which assumes the reader already knows the Agda interaction model.

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