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Tool and skill selection with decision models

Deciding which tool, skill or MCP server an agent should use for the next step. Weak matches can be declined instead of guessed.

128 public projects · page 3 of 5

  • Claude Code function hook that sends the agent's this-or-that questions to Jev and optionally ranks installed skills per prompt.

    ProjectbetaTypeScript
  • Agent toolkit for Claude Code and Codex whose optional /d router uses Jev to pick agents, skills and workflows and gate dispatch on intent.

    ProjectbetaPython
  • Open-source AI coding agent with memory and specialist agents; the list notes an optional Jev dispatch classifier.

    ProjectbetaTypeScript
  • Discontinued DeepSeek Harness decision layer whose policies let Jev only narrow permissions and fail closed; successor is jevcore.

    ProjectprototypeTypeScript
  • DeepSeek Harness jev_decide tool that brings the Jev decision paradigm to any OpenAI-compatible LLM, or to real Jev with a key.

    ProjectprototypeTypeScript
  • Six-file DSPy coding agent where Jev answers closed questions (safety, tool fit, history, delegation) and Python owns policy.

    ProjectprototypePython
  • Pairs Jev with the get-fable lifecycle harness to give coding agents fast tool and skill routing and verbatim-preserving compaction.

    ProjectprototypeTypeScript
  • Agent tool router that keeps obvious calls on a fast path, uses Jev via OpenRouter for ambiguous tool choices, and offers bounded MCTS.

    MCP serverprototypePython
  • Gives an agent one tool that uses Jev to search a nested capability tree and return only the documented commands a task needs.

    ProjectprototypeTypeScript
  • Coding agent where Jev handles context selection, tool routing, plan gating and verification, and the big model sees only key context.

    LibraryprototypePython
  • Chrome extension that converts a page's WebMCP tool schemas into Jev questions to pick a tool and fill its arguments from what you type.

    Browser extensionprototypeJavaScript
  • Chat-shaped command bar where Jev picks the tool, arguments, confirmation and reply type, and code builds replies only from tool data.

    ProjectprototypeTypeScript
  • Skill and CLI that compares a shortlist of agents, MCP servers or skills against a task and permission ceiling, abstaining on weak leads.

    MCP serverprototypeTypeScript
  • Stanley: a Jev-first coding CLI where Jev routes requests to deterministic workflows and an agent only writes new workflows when none fits.

    ProjectprototypeTypeScript
  • Experimental plugin wiring Jev into coding-agent harnesses to pick skills, tools, models and browser moves, starting with OpenCode.

    Agent skillprototypeTypeScript
  • Blender extension where Jev ranks about 2,500 operators against a plain-language request via a two-stage Choice search.

    ProjectprototypePython
  • Proof-of-concept MCP tool dispatcher that routes a natural-language command and extracts arguments using only Jev Choice and Noul.

    MCP serverprototypePython
  • Claude Code plugin that routes every subagent spawn through Jev to pick its model, effort and tool profile.

    Projectprototype
  • Node experiment where Jev picks the next step around a coding agent, with approved actions and Codex or Claude Code delegation.

    ProjectprototypeTypeScript
  • Stdlib Python dispatcher turning typed function signatures into one batched Jev request, with a browser harness against ground truth.

    ProjectprototypePython
  • Amp plugin that asks Jev to compare supplied alternatives against supplied evidence and priorities, as advisory input only.

    PluginprototypeTypeScript
  • Strict-allowlist shell harness where Jev walks a TOML decision tree to pick a bash command, flags and paths, confirming writes.

    ProjectprototypePython
  • General-purpose agent loop where Jev chooses each tool call and its arguments and Jot executes it until a reply is ready.

    ProjectprototypeTypeScript
  • Voice-controlled Mac agent where Jev picks the tool and its arguments in about 300 ms, running AppleScript or driving Chrome.

    ProjectprototypePython
  • Reads candidate logits from existing MLX-LM/VLM models on Apple Silicon to map state and a request to an allowed action.

    ProjectprototypePython
  • Phone agent where Jev picks one operation and one element from an indexed accessibility table; code does the tap.

    ProjectprototypePython
  • Grok Build fork where Jev decides once per turn which tools the chat model needs, cutting cost 14-40% in the author's tests.

    ProjectprototypeRust
  • PiJev: Pi-based coding agent where Jev shortlists skills, ranks code excerpts and triages tool failures while your model writes code.

    ProjectprototypeTypeScript
  • Experimental task router that uses Jev, skill profiles and environment checks to send requests to a rule, a skill or a large model.

    Agent skillprototypePython
  • Research runtime where every agent step is a bounded typed decision, with a paged virtual option space over tools and memory.

    ServiceresearchPython