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Heista

by co.heista

Get Dispatch Result

get_dispatch_result
Read-onlyIdempotent

Get the current status of a specialist dispatch job started via dispatch_async. Returns { status: queued|running|completed|failed, result_text?, error_text?, error_class?, retry_count, elapsed_seconds, wait_ms_hint }. Call this repeatedly after a dispatch*_async returns a job_id. Sleep wait_ms_hint milliseconds between calls. When status === "completed", read result_text as the specialist's full synthesis. When status === "failed", error_class tells you whether to retry (transient/scope/routing) or give up and synthesize around (permanent) per the fleet resilience pattern.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesThe job_id returned by a previous dispatch_<specialist>_async call.

TDQS

A4.8/5.0
Behavior5/5

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

Annotations declare readOnlyHint and idempotentHint, but description adds detailed behavioral context: the polling loop, sleep timing, and retry/give-up logic. No contradictions.

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?

Description is comprehensive but slightly long; however, every sentence adds essential operational guidance. Well-structured, starting with purpose, then return schema, then usage patterns.

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?

No output schema exists, so description fully documents the return object fields, status enum, and error handling. Covers complete lifecycle from dispatch to result interpretation.

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 coverage is 100%, so baseline 3. The description adds value by explaining the job_id's origin (from dispatch_*_async) and its role in polling, though doesn't expand on format beyond the schema's uuid pattern.

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 retrieves the status of a specialist dispatch job started via dispatch_<specialist>_async, with explicit return fields and usage pattern. It distinguishes its polling role from the async dispatch sibling tools.

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?

Provides explicit instructions: call repeatedly after dispatch_*_async returns a job_id, sleep wait_ms_hint milliseconds between calls, and interprets status values. Also specifies when to retry vs give up based on error_class, following fleet resilience pattern.

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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TDQS

A3.7/5.0
Disambiguation4/5

Despite the high tool count, most tools have distinct purposes with thorough descriptions that specify when to use each. Some overlap exists among creative direction tools (call_creative_worlds vs chat_with_creative_worlds), but the descriptions clarify usage patterns.

Naming Consistency3/5

Naming conventions are inconsistent overall: some follow verb_noun (create_powersource_url, decode_ad), others use noun_verb or compound names (adformula_intelligence, fleet_analytics_overview). However, subgroups like dispatch_* and list_*_presets maintain internal consistency.

Tool Count2/5

112 tools is far beyond the typical 3-15 range for well-scoped servers. While the server covers a broad domain, the sheer number likely overwhelms agents and suggests insufficient consolidation of related operations.

Completeness4/5

The tool set covers core creative intelligence workflows: brand analysis, ad decoding, script generation, creative direction, and research. Minor gaps exist (e.g., no social media publishing tools), but the main use cases are well-supported.

Resources