Skip to main content
Glama

Add Test Step Attachment

add_test_step_attachment

Upload evidence files to a manual test step within a test result, ensuring attachments are stored with the correct step for documentation and traceability.

Instructions

Upload evidence to a manual attachment step inside a test result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
step_nameNoOptional attachment-step name to resolve within the manual test result.
attachmentYesAttachment payload using the repo-standard pattern: {name, content_type, content? | url?}.
project_idNoOptional override for the default Project ID.
step_indexNoOptional zero-based manual step index to resolve within the test result execution.
fixture_nameNoOptional fixture name used only for the legacy fixture-step fallback.
fixture_typeNoOptional fixture type hint for the legacy fixture-step fallback: 'before' or 'after'.
attachment_idNoOptional explicit manual step attachment ID resolved from the test result execution.
output_formatNoOutput format: 'json' (default) or 'plain'.
test_result_idYesParent test result ID (required).
fixture_result_idNoOptional explicit fixture result ID for legacy fixture-step fallback.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
target_idNo
file_namesNo
status_codeNo
target_kindNo
Behavior3/5

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

Annotations already indicate this is a write operation (readOnlyHint=false). Description adds that it targets 'manual attachment steps', but doesn't disclose additional behavioral traits like error handling or step resolution logic.

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?

Single sentence, front-loaded with action and target. No unnecessary words.

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?

Despite high parameter count (10) and complex step resolution logic (step_name, step_index, attachment_id, fixture fallback), the description provides no explanation of how these parameters interact or the expected attachment payload format. Output schema exists but doesn't compensate for missing usage context.

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

Parameters3/5

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

Schema coverage is 100%, so the schema describes all parameters. The description adds no extra meaning beyond the schema's own descriptions.

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 action ('Upload evidence') and the target ('manual attachment step inside a test result'). It distinguishes from similar tools like 'add_test_result_attachment' by specifying step-level attachment.

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?

No guidance on when to use this tool versus alternatives (e.g., 'add_test_result_attachment'). No mention of prerequisites or when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ivanostanin/lucius-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server