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TeamShared

by io.github.xhad

File Upload Request

file_upload_request

Get a one-time uploader script to push a local file into a shared file.

For large local HTML/Markdown files that don't fit inline in file_create/file_update. Returns upload_url, upload_token, an expires_in_seconds TTL, and a self-deleting Python script. Save the script to disk and run python3 upload.py /path/to/file; it reads the file, POSTs it to the server with the one-time token, prints the resulting file id (and public URL if publish=true), and deletes itself on success. The token is single-use and expires in ~10 min.

Update mode: pass file_id to append the uploaded body as a new version to an existing shared file (the title is ignored; the existing file's title/slug/share_token are preserved, and the bucket mirror is re-published to the new version when the file is already published). This is the supported way to push a new version of a large file.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agentNoOverride agent identity
titleYesFile title (used only when creating a new file; ignored in update mode)
file_idNoExisting file UUID to append a new version to (update mode). Omit to create a new file.
publishNoIf true, the file is published immediately (returns public URLs). In update mode this is idempotent if already published.
work_idNoAttach the uploaded file to this work item UUID
filenameNoOptional filename (used for format sniffing and as the script's default path)
project_idNoAttach the uploaded file to this project UUID (kind=artifact)
content_formatNo'html', 'markdown', 'diagram' (teamshared.diagram/v1 JSON/YAML), or 'auto' (sniff from the file extension; *.diagram.yaml/json)auto
upload_base_urlNoOptional server origin (e.g. https://teamshared.com). Defaults to settings.public_url.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changed
    • changedInput schema / properties / content_format / description
      Previous value: -"'html', 'markdown', or 'auto' (sniff from the file extension)"New value: +"'html', 'markdown', 'diagram' (teamshared.diagram/v1 JSON/YAML), or 'auto' (sniff from the file extension; *.diagram.yaml/json)"
    • addedInput schema / properties / project_id
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Attach the uploaded file to this project UUID (kind=artifact)"
+}
  2. Changed1 schema field changed
    • addedInput schema / properties / work_id
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Attach the uploaded file to this work item UUID"
+}
  3. First observed

TDQS

A4.9/5.0
Behavior5/5

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

No annotations are provided, so the description carries the full burden, and it delivers. It discloses the one-time token, ~10-minute TTL, self-deleting script, single-use behavior, and the update-mode side effects including preserved title/slug/share_token and bucket mirror re-publishing. This is rich behavioral context that an agent needs to understand consequences before invoking.

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?

The description is well-structured and front-loaded with the core purpose, followed by a concise workflow explanation and a clearly separated "Update mode" section. Every sentence adds useful information—TTL, self-deletion, output behavior, update-mode preservation rules—without redundancy or filler.

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 9-parameter tool with an output schema, the description is complete enough: it explains the end-to-end flow (request script, save, run, upload, cleanup), the constraints, and the important update-mode behaviors. The output schema and 100% schema coverage handle remaining return and parameter details, so nothing critical is missing.

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 the baseline is 3, but the description adds meaningful semantics beyond the schema: title is ignored in update mode, file_id enables appending a new version, publish=true triggers public URL output, and filename serves as the script's default path. It doesn't narrate every parameter, but the added context materially improves parameter understanding.

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 tool's verb and resource: "Get a one-time uploader script to push a local file into a shared file." It explicitly distinguishes itself from siblings by saying it is for files that "don't fit inline in file_create/file_update," and it explains the update-mode variant. An agent can immediately tell what this tool does and how it differs from related file 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?

The description explicitly names alternatives (file_create/file_update) and states the condition for using this tool instead: large local HTML/Markdown files that don't fit inline. It also says update mode is "the supported way to push a new version of a large file," giving clear routing guidance. This leaves little to inference.

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

B3.4/5.0
Disambiguation4/5

With 104 tools across many domains (memory, work, projects, files, agents, context, strategic, ontology), the use of clear prefixes (memory_, work_, project_, file_, agent_run_, context_) makes most tools distinct. However, there are some potential confusions between memory_session_* vs memory_state_*, and memory_recall vs memory_think vs memory_assemble_context, though descriptions clarify their specific purposes. Aliases like memory_playbook_get for memory_procedure_get are explicit and reduce ambiguity.

Naming Consistency5/5

Tool names follow a highly consistent pattern: prefix_domain_action (e.g., file_create, work_update, memory_recall, agent_run_start). All use snake_case, with verbs consistently placed after the domain prefix. Even less common tools like account_brief and attention_snapshot fit the overall naming scheme, making the set predictable and easy to navigate.

Tool Count3/5

At 104 tools, this is an exceptionally large surface area, far exceeding the 25+ threshold that feels heavy. However, the server covers an extensive domain (organizational memory, work management, project tracking, file sharing, agent orchestration, and strategic planning), which justifies a large count. Still, the sheer number may overwhelm agents, and some tools could be consolidated (e.g., many memory_session_* and memory_state_* variants).

Completeness4/5

The tool surface is remarkably complete for its stated purpose, covering CRUD operations for files, work items, projects, and memory, plus lifecycle management for agents, sessions, and strategic plans. Minor gaps exist (e.g., no direct memory_item_get by ID, no section removal in projects), but agents can work around these using existing tools like memory_recall or work_create with parent_id. Overall, the set minimizes dead ends.

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