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analyze_failures

Discover common AI agent failure patterns by listing most frequent failing tools and sample error messages for targeted reliability fixes.

Instructions

Find the most common failure patterns for an agent. Returns the tools that fail most often and sample error messages.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hoursNo
limitNo
agent_idYes
Behavior3/5

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

With no annotations provided, the description carries the full burden. It does disclose that the tool returns failure counts and sample error messages, implying a read-only operation, but it does not detail any permissions, rate limits, or potential side effects. The behavioral description is minimal but non-contradictory.

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 with no filler. The first sentence states the primary action, and the second specifies the return content. Every word is purposeful.

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?

The tool is relatively simple (3 params, no output schema), and the description covers the core purpose and high-level output. However, it does not explain the semantics of the optional parameters (hours, limit) or the exact structure of the returned data, leaving gaps for an agent trying to use it correctly. Given the lack of annotations and schema descriptions, this feels adequate but not complete.

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 description coverage is 0%, so the description must compensate. It only clarifies 'agent_id' implicitly through 'for an agent', but 'hours' and 'limit' are unexplained. The parameter meanings are not conveyed beyond the default values in the schema, so the description adds minimal value here.

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 uses a specific verb 'Find' with a clear resource ('the most common failure patterns for an agent') and explicitly states the output ('tools that fail most often and sample error messages'). This clearly distinguishes it from sibling tools like get_reliability_score which suggests a numeric rating.

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

Usage Guidelines3/5

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

The description implies the tool is used for analyzing agent failures but provides no explicit guidance on when to prefer it over related tools such as get_reliability_score or recommend_improvements. There are no mentioned alternatives or exclusions, so the usage context is only implied.

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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