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SuperSkill

SuperSkill

by permanu
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

init

Destructive

Initialize superskill for the current project. Detects stack, indexes the in-repo catalog, builds the project-local knowledge graph, and registers the repo in the vault map for auto-detection. Does not scrape skills.sh.

Instructions

Initialize superskill for the current project. Detects stack, indexes the in-repo catalog, builds the project-local knowledge graph, and registers the repo in the vault map for auto-detection. Does not scrape skills.sh.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "init"
  }
}

Input Schema

NameRequiredDescriptionDefault
slugNoVault project slug for auto-detection (default: repo directory name)
bridgeNoEnable native skill bridge (replaces native skill files with superskill redirects)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.13.0
    • addedInput schema / properties / slug
      Added value: +{
+  "description": "Vault project slug for auto-detection (default: repo directory name)",
+  "type": "string"
+}
  2. First observedv0.6.1

TDQS

A3.5/5.0
Behavior3/5

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

destructiveHint=true is declared, and the description does add useful operational context (it indexes, builds a graph, and registers the repo — all non-trivial side effects). However, it never explains WHY the operation is destructive or what existing state it overwrites, so the destructive annotation is left unelaborated.

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?

Front-loaded with the primary action, followed by a compact comma-list of steps and a one-clause exclusion. Minimal waste, though the step enumeration is slightly dense for a single sentence.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a setup/mutation tool with no output schema, the description covers what it does and its scope boundary well. Its main gap is not clarifying the destructive nature flagged by annotations, but otherwise an agent has enough to invoke it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so slug and bridge are already fully documented in the schema. The description adds nothing about either parameter, so the baseline 3 applies when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (Initialize) and resource (superskill for the current project), then enumerates the concrete operations: stack detection, catalog indexing, knowledge-graph build, vault registration. The negative scope ("Does not scrape skills.sh") further bounds it, though it doesn't name a specific sibling alternative for contrast.

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

Usage Guidelines3/5

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

The phrase "for the current project" and "auto-detection" imply this is first-time project setup, but there is no explicit when-to-use, no prerequisites, and no comparison against siblings like knowledge_rebuild or register. Usage context is only inferred.

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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