intent-engineering
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| audit_intent_specA | Audit an intent spec against the 25-item validation checklist and the 5 fatal anti-patterns from the intent-engineering skill. Provide either spec_text (raw spec) OR file_path (absolute path to a markdown or YAML file). For long inputs, use start_index + max_length to paginate; the response includes next_chunk_token when more content remains. |
| generate_intent_spec_scaffoldA | Return the appropriate intent-spec template (blank, Level-1 MVR, or full 9-section) with optional pre-filled objective_hint, autonomy_level, and agent_name. Use this when starting a new agent/skill or retrofitting an existing one. |
| assess_retrofit_levelA | Look at an existing prompt or SKILL.md and recommend the right retrofit level (L1-mvr / L2-structured / L3-full) with reasoning grounded in the intent-engineering skill's blast-radius / complexity / autonomy framework. Provide either skill_text (raw text) OR file_path (absolute path to an existing SKILL.md or prompt file). |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: auditing, generating scaffolds, and assessing retrofit levels. No overlap in functionality.
All tool names follow a consistent verb_noun pattern (audit_, generate_, assess_), making it easy to predict their actions.
Three tools is on the low side but appropriate for a focused domain like intent engineering. Each tool provides substantial functionality (e.g., pagination, multiple input options).
The tools cover core workflows: creating, auditing, and upgrading intent specs. Missing a direct editing tool, but scaffold generation and audit cover most needs.