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v0.4.0 adds contract-safe tooling for MCP, OpenAI function, Anthropic, and generic tool schemas: provider-aware adapters, deterministic canonical JSON, SHA-256 fingerprints, exact-equivalence checks, and schema inspection. Raw execution schemas remain authoritative. Tool retrieval is research-only and is never used for authorization or execution.
Tool definitions are context—and unlike ordinary prompt text, they are execution contracts.
LLMSlim v0.4.0 makes tool-schema handling easier to inspect and reason about: preserve raw definitions, create deterministic canonical views, fingerprint complete contracts, and verify exact equivalence before measuring catalog representations.
We also published the uneventful result: across 375 schemas in 18 catalogs, lossless measurement saved 0 tokens because the baseline was already compact canonical JSON. That’s useful evidence, not a hidden failure. Experimental retrieval remains research-only and is never an authorization or execution decision.
I’d love feedback from builders using MCP or multi-provider tools: where do adapters break fidelity, and how are you tracking contract changes across catalogs?
Install: `pip install llmslim`
Release notes: https://github.com/Thanatos9404/...
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About LLMSlim on Product Hunt
“Tool-aware context, contract-safe.”
LLMSlim was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #86 on the daily leaderboard. v0.4.0 adds contract-safe tooling for MCP, OpenAI function, Anthropic, and generic tool schemas: provider-aware adapters, deterministic canonical JSON, SHA-256 fingerprints, exact-equivalence checks, and schema inspection. Raw execution schemas remain authoritative. Tool retrieval is research-only and is never used for authorization or execution.
LLMSlim was featured in Developer Tools (518.5k followers) on Product Hunt. Together, these topics include over 81.6k products, making this a competitive space to launch in.
Who hunted LLMSlim?
LLMSlim was hunted by Yashvardhan Thanvi. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Yashvardhan Thanvi