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find_missed_spawns

Read-only

Find assistant responses decomposable into independent blocks but answered without spawn() calls, calibrating spawn_hint strength.

Instructions

Find assistant responses that decomposed into independent blocks but were answered linearly (no spawn() call nearby).

Algorithm:

  1. Pull recent assistant messages (last window_days days, length ≥ min_response_len, excluding subagent jsonls).

  2. For each, count top-level numbered items and H2/H3 headers.

  3. Mark as decomposable if numbered ≥ min_numbered OR headers ≥ min_headers.

  4. For each decomposable response, check whether any tasks row with parent_cid = response's session_id has started_at within ±10 min of the response. If none → missed_spawn.

  5. Return top top_n by score (numbered + headers).

Use this to calibrate the spawn_hint: a high missed-spawn count means the hint isn't strong enough, or thresholds need tuning.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
top_nNo
min_headersNo
window_daysNo
max_messagesNo
min_numberedNo
min_response_lenNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Describes the algorithm step-by-step, detailing how responses are analyzed and missed spawns detected. Adds significant behavioral context beyond the readOnlyHint annotation.

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?

Well-structured with summary, algorithm steps, and usage. Though lengthy, it earns its place for a complex tool. Front-loaded with purpose.

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?

Covers purpose, algorithm, usage, and parameters. Output schema exists so return values need not be described. Complete for the tool's complexity.

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?

Describes most parameters (window_days, min_response_len, min_numbered, min_headers, top_n) within the algorithm, adding meaning. Does not mention max_messages, but overall adds value.

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 it finds assistant responses that decomposed into independent blocks but were answered linearly, distinguishing it from siblings like spawn and spawn_status.

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

Usage Guidelines4/5

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

Explicitly states 'Use this to calibrate the spawn_hint', providing clear usage context. Does not mention when not to use or alternatives but gives sufficient guidance.

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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