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Request OpenAkashic Note Publication

request_note_publication

Request librarian review for public publication. Source remains private by default.

For kind='claim', the normal submission flow is:
private + publication_status=requested -> guardrail check ->
guardrail_passed or guardrail_rejected -> published if later approved.
Use claim_contribution_status(path=...) to inspect that state.
Formerly known as `check_contribution_status`. If you see tool-not-found
errors, use claim_contribution_status instead.

Provide `rationale` (or `reason` alias) explaining WHY the note is publication-worthy,
plus `evidence_paths` linking supporting notes. Weak requests (empty rationale or
evidence) are accepted but returned with `warnings` so the caller can improve them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesExact path of the note to publish. Use the `path` value returned by upsert_note — do not guess or reconstruct it. Example: 'personal_vault/projects/my-project/findings.md'
reasonNoAlias for rationale — use either field.
rationaleNoWhy this note is worth making public (≥20 chars). Be specific — vague rationale causes rejection. Example: 'Benchmark results with reproducible code showing 1.14x speedup of list comprehensions vs for-loops on 1M elements.'
requesterNoYour username. If omitted, inferred from your auth token.
evidence_pathsNoPaths or URLs supporting this note's claims. Example: ['personal_vault/projects/my-project/evidence.md', 'https://docs.python.org/3/library/timeit.html']. Required for approval.
target_visibilityNoTarget visibility after approval. Use 'public' (default).public

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

No annotations are present, so the description carries the full transparency burden. It discloses the guardrail state machine, that source remains private by default, that weak requests are accepted but return warnings, and that the tool was formerly known as check_contribution_status. This is rich, useful behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with a clear purpose statement and remains focused. The state-machine explanation and alias guidance are relevant, and there is no filler, though the flow details make it slightly denser than necessary.

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?

With six parameters and an output schema present, the description still provides crucial context: the submission flow, how to monitor state via claim_contribution_status, input expectations for rationale and evidence_paths, and warning behavior. This is sufficient for an agent to select and invoke the tool 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?

Schema coverage is 100%, so a baseline of 3 applies. The description adds value beyond the schema by explaining the rationale/reason alias, clarifying that evidence_paths link supporting notes, and warning that weak requests are accepted with warnings. This is meaningful but not exhaustive.

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 opens with 'Request librarian review for public publication,' giving a specific verb and resource. It adds 'Source remains private by default' to clarify scope, and explicitly distinguishes itself from the status-inspection sibling by naming claim_contribution_status.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a concrete workflow for kind='claim' and directs the caller to use claim_contribution_status(path=...) to inspect state, including a former-name alias to avoid tool-not-found errors. It does not explicitly compare with sibling set_note_publication_status but gives enough contextual guidance for correct use.

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

A3.5/5.0
Disambiguation4/5

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.

Naming Consistency5/5

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.

Tool Count2/5

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.

Completeness5/5

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.