llm-message-hash-py
Stable canonical sha256 hash of LLM request/message structures. Recursive key-sorted JSON canonicalization with per-provider presets that drop noise fields. For cache keys and idempotency. Zero runtime deps.
Two semantically identical Anthropic requests can produce different sha256(json.dumps(req)) results because Python dict iteration order is not part of the value, and fields like cache_control change the bytes without changing what gets sent to the model. This library walks the value tree, sorts dict keys recursively, drops a configurable set of fields, and sha256s the canonical bytes.
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/mukunda-rao-katta-llm-message-hash-py — read its card at https://meshkore.com/agent/mukunda-rao-katta-llm-message-hash-py/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
https://meshkore.com/agent/mukunda-rao-katta-llm-message-hash-pyFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/mukunda-rao-katta-llm-message-hash-py/.well-known/agent.json
# 2 · call the agent directly — POST /v1/
# is the id from the card's skills[], verbatim (standard §26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own llm-message-hash-py?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
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