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Metis — Start Span

start_span

Open a new tracing span and receive a span_id to later close with end_span, enabling nested spans and performance tracking.

Instructions

Open a new tracing span. Returns the span_id to pass to end_span().

Args:
    name:       Human-readable span label (e.g. 'stage_1_bootstrap', 'tool:search_library').
    kind:       Span type — 'internal' | 'tool' | 'agent' | 'llm'. Default: 'internal'.
    session_id: Session identifier (from session_bootstrap). Optional.
    run_id:     FK to agent_runs.run_id. Optional.
    parent_id:  Parent span_id for nested spans. Optional.
    tags:       JSON string of extra key/value metadata. Optional.

Returns the span_id string — pass it to end_span() when the work is done.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNointernal
nameYes
tagsNo
run_idNo
parent_idNo
session_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description adequately discloses that the tool creates a span and returns an identifier. It notes the need to call end_span, which is a key behavioral trait. Could mention potential side effects (e.g., memory/performance) but the simplicity of the operation makes this sufficient.

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 well-structured with a clear opening sentence followed by a bullet-style Args list and a Returns line. It is somewhat verbose given the tool's simplicity, but every sentence earns its place.

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 presence of an output schema (which likely defines the span_id return type), the description covers all necessary context: purpose, parameter details, return value, and the required follow-up call (end_span). It is complete for an AI agent.

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

Parameters5/5

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

Schema description coverage is 0%, so the description fully compensates by explaining each parameter's meaning, defaults, and examples (e.g., 'name: Human-readable span label... kind: Span type...'). This adds significant value beyond the raw schema.

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 states the verb ('Open a new tracing span') and the resource ('span'), and distinguishes it from sibling tools like 'end_span' and 'get_spans' by focusing on creation and returning a span_id.

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 a usage flow (pass span_id to end_span) but does not explicitly state when to use this tool versus alternatives, nor does it provide conditions, prerequisites, or exclusions.

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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