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timps_monitoring_agent

Generate Prometheus metric definitions, Grafana dashboard JSON, alerting rules, and instrumentation code snippets for service monitoring.

Instructions

Generate Prometheus metric definitions, Grafana dashboard JSON, alerting rules, and instrumentation code snippets.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slosNoe.g. ['p99 < 200ms', 'error_rate < 0.1%']
languageNopython
alerting_platformNoalertmanager
service_descriptionYes
Behavior2/5

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits, but it only lists outputs and gives no indication of side effects (e.g., whether it makes network calls, requires authentication, or has side effects). It doesn't disclose return format, potential side effects, or any operational behavior beyond 'generate'. This is a significant gap for a tool that could be expected to interact with external monitoring systems.

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?

The description is a single, well-structured sentence that efficiently enumerates the tool's outputs. It has no redundant words and immediately conveys the core function. Every part is necessary.

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?

Given the tool's moderate complexity (4 parameters, multiple output types) and the absence of annotations and output schema, the description is under-specified. It doesn't clarify how the tool decides which artifacts to generate, what the expected behavior with no 'slos' is, or how language/alerting_platform affect the output. The description is too terse to be considered complete for this generation tool.

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

Parameters1/5

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

The description adds zero parameter-related information. With schema coverage at only 25% (only one of four parameters has a description in the schema), the description's complete silence on parameters such as 'slos', 'language', and 'alerting_platform' leaves the agent without adequate context to use the tool correctly. The description fails to compensate for the sparse schema.

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 uses a strong imperative verb 'Generate' and lists specific artifacts (Prometheus metric definitions, Grafana dashboard JSON, alerting rules, instrumentation code snippets), making the tool's core purpose clear and distinct from many unrelated siblings. However, it does not explicitly differentiate itself from closely related tools like timps_observability_cost_optimizer or timps_model_perf_monitor, so it falls slightly short of a 5.

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?

The description provides no guidance on when to use this tool versus alternatives. It merely states what it generates, without any context on use cases, prerequisites, or scenarios where another tool might be more appropriate. No exclusions or alternative tool references are given.

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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