upload_imageUpload an image into OpenAkashic assets and return embeddable markdown.
| Name | Required | Description | Default |
|---|---|---|---|
| alt | No | ||
| folder | No | assets/images | |
| filename | Yes | ||
| content_base64 | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose the return type (embeddable markdown), but it does not mention any side effects, authentication requirements, file type restrictions, overwriting behavior, or other operational details that would be expected for an upload/mutation tool. This is a significant gap.
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?
The description is a single sentence that immediately states the core function. It is concise, front-loaded with the verb, and contains no filler or redundant 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?
The tool has moderate complexity with four parameters and no annotations. Although an output schema exists (so return values are covered), the description omits critical context such as parameter meanings, usage nuances, and any behavioral constraints. This is insufficient for correct invocation, especially given the 0% schema description coverage.
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?
The schema has 0% description coverage and the description does not explain any of the four parameters (filename, content_base64, folder, alt). The description adds no meaning beyond the property names themselves, and for required parameters like content_base64, a format or encoding explanation is missing. The description fails to compensate for the schema's lack of detail.
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 clearly states the action ('Upload an image'), the resource ('into OpenAkashic assets'), and the outcome ('return embeddable markdown'). This is specific and distinguishes from sibling tools, none of which involve uploading images. The title reinforces the purpose.
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 description implies usage when one needs to upload an image into OpenAkashic assets, but it does not explicitly state when to use this tool vs alternatives, nor does it mention any prerequisites or exclusions. There are no direct alternative upload tools among siblings, so the implied usage is acceptable but not explicit.
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.
Most tools have clear, distinct purposes, but there are overlapping areas such as search_akashic vs search_notes vs search_and_read_top, and confirm_note/dispute_note/review_note which serve related but different review functions. Descriptions are detailed enough to reduce ambiguity, though some boundary cases require careful reading.
All tool names follow a consistent snake_case verb_noun pattern (e.g., list_notes, create_folder, delete_note, move_note). Even debug tools and compound names like search_and_read_top maintain the convention. The only exception is whoami, which is a common standalone verb and does not break the overall pattern.
With 35 tools, the server has a large surface area that could overwhelm agents. The tool count exceeds the 25+ threshold for 'too many' in the rubric, even though the broad domain (notes, folders, search, reviews, publication workflow, debugging) partially justifies the number. The set feels heavy and could benefit from consolidation.
The toolset provides thorough coverage of the knowledge management lifecycle: note CRUD (upsert/read/delete/move), folder management, multiple search modes, review/confirmation/dispute mechanisms, publication workflow, stale note handling, image upload, and debugging utilities. There are no obvious dead ends; every major operation needed to manage and publish notes is represented.