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get_answer

Answers developer questions about a codebase with cited, confidence-rated synthesis from hybrid retrieval, in one round-trip.

Instructions

Synthesised answer with citations and a calibrated trust signal.

The single entry point for questions: "how does X work" / "where is Y" /
"why is Z". It runs the full hybrid retrieval internally (no prior
search_codebase call needed) and answers in one round-trip.
confidence=high is content-grounded (value + citation-source + frame
gates): cite it directly, no verification Read needed. A "why" answer
whose named mechanism is absent from the retrieved source is downgraded
to medium (the rationale may be conflated). Low confidence returns
best_guesses with one-line justifications instead of an empty answer.
retrieval_quality separately rates the retrieval that fed synthesis.
When the answer names a function/method/class, ``symbol_bodies`` carries
its full live body — read that instead of a follow-up get_symbol.
``episodes``, when present, is a dated fact recorded about this checkout
that bears on the question — evidence beside the answer, not a correction
of it. Weigh it against the answer; ``still_true`` says how current it is.

Args:
    question: developer question.
    scope: optional path-prefix filter (e.g. "src/pkg/").
    repo: usually omitted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoNo
scopeNo
questionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it excels. It explains the confidence=high gating (content-grounded, can cite directly), downgrade to medium for 'why' answers with missing mechanisms, low-confidence best_guesses behavior, retrieval_quality rating, and the meaning of symbol_bodies and episodes including the still_true field. Each behavior is tied to how the agent should interpret or use the result.

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 longer than the ideal, but every sentence carries operational value, and the structure is coherent (synthesized answer definition, trust/confidence semantics, symbol_bodies, episodes, then Args). It is front-loaded with the core purpose and key qualifier ('single entry point'), and the Args section is cleanly separated. A slightly more concise version might tighten the prose, but no sentence is wasted.

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 tool's complexity (multi-part response with confidence, citations, symbol bodies, episodes, still_true), the description covers virtually all aspects an agent needs: how to interpret confidence levels, what to do with symbol_bodies, how to weigh episodes, and what parameters are expected. The output schema existence is noted, so return values need not be enumerated, and the description still explains the key fields, making it complete for safe invocation and result processing.

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 input schema has 0% description coverage, but the description's 'Args' section adds meaning: question is a developer question, scope is an optional path-prefix filter, and repo is 'usually omitted'. This gives practical guidance (e.g., when to omit repo) that the schema alone does not. It doesn't elaborate on exact formats or examples, but it compensates well for the schema gap.

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 identifies the tool as a question-answering entry point for developer questions ('how does X work' / 'where is Y' / 'why is Z'), with a specific verb ('answers') and resource ('synthesised answer with citations'). It distinguishes itself from siblings by stating it is 'the single entry point for questions' and explicitly notes it runs retrieval internally, eliminating the need for a prior search_codebase call, and contrasts with get_symbol for symbol bodies.

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?

The description provides strong usage guidance: it declares this as the single entry point for questions, says no prior search_codebase call is needed, and recommends reading symbol_bodies instead of a follow-up get_symbol when a function is named. It lacks explicit when-not-to-use guidance for other siblings (e.g., when to prefer search_codebase over get_answer for pure code search), which would make it a 5.

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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