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dialectic_review

Retrieve active claims from the dialectic graph, filtering by minimum confidence level and optional domain. Omitted retired and superseded claims.

Instructions

List active claims filtered by confidence floor and optional domain. Retired/superseded claims are omitted.

min_confidence: one of 'low','medium','high','disputed'. Note that 'disputed' is treated as its own bucket (not ordered against the others) — passing min_confidence='disputed' returns only disputed.

Format: ' [conf] tier= domain= support=N contradict=N '.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
min_confidenceNolow
domainNo
kNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries full burden. It discloses that retired/superseded claims are omitted and explains the unusual 'disputed' bucket behavior, which is beyond what the schema provides. However, it does not explicitly state that the operation is read-only or describe any side effects, missing an opportunity for full transparency.

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 efficient and well-structured: a clear purpose statement followed by parameter details and output format. Every sentence adds value, with no redundant text. However, the output format could be integrated more seamlessly.

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

Completeness3/5

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

Given the tool's simplicity, the description covers the core functionality (listing filtered claims) and provides output format. However, it lacks explanation for the 'k' parameter (likely a limit) and does not clarify how 'domain' values are specified. An output schema exists but isn't shown; the description partially compensates.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate. It adequately explains the 'min_confidence' parameter, including the special 'disputed' bucket, but only mentions 'domain' as 'optional domain' without further detail, and says nothing about 'k'. With 3 parameters, only one is well-described, leaving significant gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

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

The description clearly states it lists active claims filtered by confidence floor and domain, which is a specific verb+resource. It distinguishes from siblings like 'dialectic_claim' (creates claims) and 'dialectic_evidence' (adds evidence) by focusing on listing. However, the tool name 'dialectic_review' might imply broader review than just listing, slightly reducing clarity.

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 explicit guidance on when to use this tool versus alternatives. While it mentions that retired/superseded claims are omitted, it does not specify when other tools (e.g., 'candidate_review_status', 'curator_review') should be used instead. The context of use is only implied through filtering options.

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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