get_datafileGet a single datafile by slug or id, including its JSON content and last published CDN path.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | No | the datafile slug (provide this or datafile_id) | |
| datafile_id | No | the datafile id (provide this or slug) |
| Name | Required | Description | Default |
|---|---|---|---|
| json | No | ||
| slug | Yes | ||
| schema_id | No | ||
| datafile_id | Yes | ||
| description | Yes | ||
| display_name | Yes | ||
| content_sha256 | No | ||
| last_published_path | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered without the description. The description adds useful response-context (includes JSON content and last published CDN path) but does not disclose behavior around identifier conflicts or missing identifiers; this is consistent with the annotations, and the added value is modest.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single 15-word sentence that front-loads the verb and resource and packs the identification method and key return values into the remainder. There is no filler and no repetition of schema content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity read tool, the description plus a 100%-covered schema, safety annotations, and an existing output schema cover nearly everything an agent needs to call it correctly. The only minor gap is edge-case behavior when both slug and datafile_id are provided, which the schema hints at but the description does not settle.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the schema descriptions already capture the either/or constraint ('provide this or datafile_id' / 'provide this or slug'). The description's 'by slug or id' reiterates the schema rather than adding new semantics, so the baseline 3 applies because the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Get'), a specific resource ('single datafile'), and the two identification routes (slug or id). It adds return-content detail ('JSON content and last published CDN path'), and the 'single' qualifier distinguishes it from list_datafiles and the many other get_* siblings targeting different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The 'by slug or id' phrasing implies the agent should call this when it already holds a datafile identifier and wants the record's full content, but no alternative tool is named and no when-not-to-use condition is given. There is no explicit routing toward list_datafiles for multi-record needs, so usage guidance is implied rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Every resource family follows the same verb+noun pattern and each tool name uniquely identifies a resource-action pair (create_app vs create_app_version vs update_app vs publish_app). Closest overlaps like analyze_resource vs get_resource_graph and patch_datafile vs update_datafile are explicitly differentiated by their descriptions, so misselection risk is low despite the scale.
Names are almost uniformly verb_noun snake_case with a consistent lifecycle vocabulary: create/get/update/delete/list/publish/unpublish/version. Minor outliers like whoami and run_schedule_now are idiomatic and do not break the predictability of the set.
At 93 tools this far exceeds the calibration's 50+ extreme-mismatch case. The count is inflated by repeating create/get/update/delete/version/publish/unpublish across ten resource families; even though each family is systematic, the combined surface is very hard for an agent to navigate and keep in context.
Core CRUD/publish/version lifecycles are present for apps, workflows, endpoints, schedules, schemas, datafiles, and api templates, and dependency analysis is well covered. However, secret creation/updating, asset upload, custom-domain deletion, and version-range enumeration for several resource types are absent or left to the external dashboard, so agents hit a few manual dead ends.