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context_health

Analyze conversation health by detecting conflicts, ambiguity, grounding issues, and context drift to maintain consistency in AI interactions.

Instructions

[CONTEXT & STATE] 13 sub-tools: recap, conflict, ambiguity, verify, entropy, abstention, grounding, drift, depth, get_state, set_state, clear_state, history. Auto-selects based on params or use 'check' to override. TIP: context_loop runs all health checks automatically — prefer context_loop for comprehensive analysis, use context_health for targeted checks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sessionIdNoSession identifierdefault
checkNoOverride: run a specific check. If omitted, auto-selects based on params. clear_state shares params with get_state — use this override to disambiguate.
paramsNoParameters for the underlying tool(s), minus sessionId. Multiple checks run if params match more than one tool. recap: {messages[], lookbackTurns?}; conflict: {newMessage}; ambiguity: {requirement, context?}; verify: {goal, output, expectedIndicators?}; entropy: {outputs[], threshold?, autoReset?}; abstention: {claim, requiredKeys[], threshold?}; grounding: {assistantOutput, claim?}; drift: {windowSize, turn?, health?, breakdown?}; depth: {content, minDepthWords?, minDepthSentences?}; get_state: {keys?}; set_state: {key, value, source?}; clear_state: (use check override); history: {maxTokens}
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions 'auto-selects based on params' and the override capability, but doesn't disclose critical behavioral traits like what happens when multiple checks run, error handling, performance characteristics, or what 'health' assessment entails.

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?

Reasonably concise with two sentences plus a TIP. The first sentence is dense but informative. Could be slightly more front-loaded with purpose before implementation details.

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 3 parameters, 100% schema coverage, no output schema, and no annotations, the description provides good usage guidance but lacks behavioral context for a complex tool with 13 sub-tools. The absence of output schema means the description should ideally explain what results to expect.

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?

Schema description coverage is 100%, so baseline is 3. The description adds meaningful context about 'clear_state shares params with get_state — use this override to disambiguate' and mentions 'Multiple checks run if params match more than one tool,' which provides valuable semantic information beyond the schema.

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?

The description states the tool has '13 sub-tools' for health checks and can auto-select or override, but it's vague about what 'health' means in this context. It distinguishes from sibling 'context_loop' but doesn't clearly articulate the core purpose beyond being a collection of checks.

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

Usage Guidelines5/5

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

Explicitly provides when-to-use guidance: 'prefer context_loop for comprehensive analysis, use context_health for targeted checks.' This clearly distinguishes from the sibling tool and gives specific usage context.

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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