MisakaNet

misakanet_write_lesson

[STRUCTURED COMMIT / VALIDATED SUBMISSION] Submit a complete, structured failure lesson (title/domain/problem/root_cause/fix) as a formal submission. Requires authentication (Bearer token in header) — this is the 'validated author' path, not open triage. Output goes through lesson-gate/lint/review and becomes a versioned lesson in the git repo. For quick open reports when you only have a partial failure description, use misakanet_submit_intake instead (no Bearer). Lessons are immutable once merged — corrections go through a new intake/PR, so there is intentionally no misakanet_update_lesson/misakanet_delete_lesson. Returns: object {lesson_id: string, status: 'pending_review', quality_score: number}; or {submitted: false, error}. Example: misakanet_write_lesson(title='pip timeout behind proxy', domain='python', problem='...', root_cause='...', fix='...')

Input Schema

TableJSON Schema

Name	Required	Description
`fix`	Yes	How to fix it (required).
`tags`	No	Comma-separated tags.
`title`	Yes	Short descriptive title.
`domain`	Yes	Domain: devops, python, network, feishu, rag, fanuc, mcp, etc.
`source`	No	Source: codex, claude-code, cursor, etc.
`problem`	Yes	What failed (required).
`root_cause`	Yes	Why it failed (required).
`verification`	No	How to confirm the fix works.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`error`	No
`status`	No
`lesson_id`	No
`submitted`	No
`quality_score`	No

Schema Changelog

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

Changed1 schema field changedSep 3, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "error": {
+      "type": "string"
+    },
+    "lesson_id": {
+      "type": "string"
+    },
+    "quality_score": {
+      "type": "number"
+    },
+    "status": {
+      "type": "string"
+    },
+    "submitted": {
+      "type": "boolean"
+    }
+  },
+  "type": "object"
+}

First observedAug 29, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Beyond the all-false annotations, the description discloses substantial behavior: required Bearer auth, lesson-gate/lint/review pipeline, git versioning, immutability after merge, intentional absence of update/delete, and the exact return shape. This is much richer behavioral context than annotations alone and nothing contradicts the annotations.

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 dense but every clause earns its place: scope, auth requirement, pipeline behavior, sibling alternative, immutability constraint, return type, and example. The essential validation criteria are front-loaded and the prose is well structured.

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 write/submission tool with 8 parameters and a complex workflow, this description covers required fields, optional path selection, auth, post-submission processing, immutability, correction path, and return contract. Nothing an agent needs to call or reason about this tool 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 already documents all 8 parameters with clear descriptions, so the baseline is 3. The description adds a concrete invocation example with real values and groups title/domain/problem/root_cause/fix as the core complete-lesson fields, giving agents a model for how to populate them.

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 'Submit a complete, structured failure lesson' and names the exact resource and required fields (title/domain/problem/root_cause/fix). It positions the tool as the formal 'validated author' submission path and explicitly distinguishes it from the quick-intake sibling, so an agent can identify it accurately.

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?

It explicitly states when to use this tool (complete structured lesson, Bearer-token validated author) and when not to (partial failure description -> misakanet_submit_intake, no Bearer). It also explains the correction workflow via a new intake/PR because lessons are immutable, leaving no ambiguity about updating.

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

All MisakaNet tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.6/5.0

Disambiguation5/5

Each tool has a distinct role: retrieval (search/get_lesson), submission (submit_intake/write_lesson), evidence (me_events), risk preflight, and registration. The two submission tools are carefully differentiated by structure and auth requirements, so an agent should not confuse them.

Naming Consistency4/5

All tools share the misakanet_ prefix and snake_case style, and most use a verb_noun pattern. Minor deviations like search, register, preflight, and me_events break the pattern slightly, but the names remain readable and predictable.

Tool Count5/5

Seven tools is well-scoped for a failure-lesson registry: one onboarding tool, one guardrail, two read paths, two submission paths, and one evidence-check tool. No tool feels redundant or missing at a coarse level.

Completeness5/5

The lifecycle is covered end-to-end: register for access, search and get lessons, submit either partial intakes or structured lessons, preflight risky actions, and check reuse evidence. Update/delete are intentionally absent because lessons are immutable, and corrections route through intake, so there are no dead ends.

Resources

Need Help?