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Glama
smat-dev

Jinni: Bring Your Project Into Context

by smat-dev

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

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

Server capabilities have not been inspected yet.

Tools

Functions exposed to the LLM to take actions

NameDescription
usageA

Retrieves the Jinni usage documentation (content of README.md).

read_contextA

Reads context from a specified project root directory (absolute path). Focuses on the specified target files/directories within that root. Returns a static view of files with paths relative to the project root. Assume the user wants to read in context for the whole project unless otherwise specified - do not ask the user for clarification if just asked to read context. If the user just says 'jinni', interpret that as read_context. If the user asks to list context, use the list_only argument. Both targets and rules accept a JSON array of strings. The project_root, targets, and rules arguments are mandatory. You can ignore the other arguments by default. IMPORTANT NOTE ON RULES: Ensure you understand the rule syntax (details available via the usage tool) before providing specific rules. Using rules=[] is recommended if unsure, as this uses sensible defaults.

Guidance for AI Model Usage

When requesting context using this tool:

  • Default Behavior: If you provide an empty rules list ([]), Jinni uses sensible default exclusions (like .git, node_modules, __pycache__, common binary types) combined with any project-specific .contextfiles. This usually provides the "canonical context" - files developers typically track in version control. Assume this is what the users wants if they just ask to read context.

  • Targeting Specific Files: If you have a list of specific files you need (e.g., ["src/main.py", "README.md"]), provide them in the targets list. This is efficient and precise, quicker than reading one by one.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A3.9/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have completely distinct purposes: 'read_context' is for reading project files and directories, while 'usage' is for retrieving documentation. There is no overlap or ambiguity between them; an agent would never confuse one for the other.

Naming Consistency4/5

Both tools use snake_case naming, which is consistent. However, 'read_context' follows a verb_noun pattern, while 'usage' is a noun only, representing a minor deviation from a fully uniform convention.

Tool Count2/5

With only 2 tools, the server feels thin for its purpose of bringing projects into context. While 'read_context' is core, there are likely missing operations like updating context, managing rules, or querying context metadata, making the set under-scoped.

Completeness2/5

The tool surface is severely incomplete for the domain of project context management. It only supports reading context and accessing documentation, lacking essential operations such as writing/modifying context, listing available contexts, or configuring rules beyond defaults, which will limit agent capabilities.

Maintenance

ActivityInactive
ResponsivenessNo issues