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Read an artifact's body

get_artifact
Read-only

Read the actual text of an artifact another teammate attached to a task. get_task lists artifacts and inlines small text bodies; use this when a body was truncated or omitted, or to fetch one artifact by id or by task_id + name. Binary artifacts come back with a short-lived download_url instead of text. A synthesizer must read its inputs with this tool before reconciling them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoArtifact name/filename within that task.
task_idNoTask id — use with `name` when you don't have the artifact id.
max_bytesNoInline body cap in bytes. Default 200000.
artifact_idNoArtifact id (from get_task's artifacts list).

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already mark the tool read-only and non-destructive; the description adds behavior beyond that: binary artifacts return a short-lived download_url instead of text, and get_task's inlined bodies can be truncated, making this the way to get the full text. This is useful operational context, though auth and error behavior are not addressed.

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?

Four sentences, each earning its place: the core operation, the get_task alternative and its limitation, binary handling, and the synthesizer requirement. The key differentiator is front-loaded.

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?

For a read-only fetch tool with no output schema, the description covers return behavior (text vs short-lived download_url), lookup modes, the relationship to get_task, and truncation semantics. Nothing esseential is missing for an agent to select and invoke it correctly.

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?

All four parameters are already fully documented in the schema, so the baseline is 3; the description adds meaningful relationship guidance by presenting the two lookup modes (artifact_id vs task_id + name) and explaining the truncation situation that max_bytes controls. This helps an agent choose the right parameter combination.

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 names a specific verb and resource: read the actual text/body of an artifact attached to a task. It also distinguishes itself from get_task, which lists artifacts and inlines small bodies, so the agent can tell the tools apart.

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?

It explicitly states when to use this tool: when a body was truncated or omitted, or to fetch one artifact by id or task_id + name. It names get_task as the alternative that inlines small bodies, and it adds a role-specific mandate for synthesizers.

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
Disambiguation3/5

Most tools target a distinct resource and action, but several adjacent pairs are easy to confuse: add_comment vs add_progress_note, call_executor vs call_integration, log_client_decision vs update_client_context vs memory_save, and list_context_sources vs list_integrations. The descriptions do disambiguate them, but the boundaries are subtle enough that misselection is likely with 81 tools.

Naming Consistency4/5

The overwhelming majority follow a clear verb_noun snake_case pattern (create_task, update_project, list_integrations, set_webhook), and get_/ list_/ create_/ update_ families are predictable. Minor deviations exist: memory_read/memory_save/memory_search invert to object_verb, and bare nouns like whoami, glossary, and security_posture break the pattern, but there is no chaotic casing or mixed conventions.

Tool Count2/5

At 81 tools, this is far above the weight that is comfortable for an agent's tool-selection surface, especially since many tools belong to families that could be consolidated (webhooks, worker keys, project logs, context/memory). Although the domain is broad, the count will overwhelm agents and increase misrouting.

Completeness4/5

The surface is unusually comprehensive: tasks, projects, workers, leases, artifacts, comments, handoffs, webhooks, keys, context, memory, integrations, and support all have create/read/update/delete or equivalent lifecycle coverage. The gaps are minor, such as remove_dependency without a visible add_dependency and no artifact/comment deletion, but agents can work around them.

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