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Engineering Decision Intelligence
ExplanationVersion 0.2.0

LCA Skills host support and qualification

Use explicit structural, runtime, host, and scientific evidence labels instead of a generic supported/unsupported claim.

Qualification vocabulary

StatusMeaning
NOT_TESTEDNo representative evidence
NOT_INSTALLEDRequired component is absent
DETECTED_UNQUALIFIEDComponent exists, but no successful representative run
STRUCTURALLY_QUALIFIEDPackage/frontmatter/references/hashes pass static checks
RUNTIME_TESTEDA representative local command executed successfully
HOST_TESTEDPackage was imported and invoked in the named host/version
SCIENTIFICALLY_QUALIFIEDKnown-case model semantics/results and seeded failures passed with practitioner review
FAILTested behavior did not meet acceptance criteria

Current package evidence boundary

Host/packageCurrent evidence boundary
ChatGPT upload packageStructurally qualified; scan/install/activation/artifact behavior still requires evidence from the target account/workspace before HOST_TESTED
Claude.ai upload packageStructurally qualified; upload/activation/code-execution behavior remains host-specific
Claude Code pluginStructurally qualified package with skills, agents, hook, and MCP config; the actual Claude Code build still needs host testing
Claude Code standaloneStructurally qualified; install/invocation must be tested on the target machine
Codex packageStructurally qualified; import workflow and invocation syntax must be confirmed in the actual Codex host/version
Generic Agent Skills hostPortable package shape; host-specific import/invocation evidence is still required

A skill package does not grant external-system access

Installing LCA Skills does not automatically grant access to desktop openLCA, local Brightway projects, GREET files, licensed databases, or private files. External-system access requires an explicit connector/app/MCP path and its own permissions and qualification.

Minimum host test

  1. Record host and version.
  2. Verify package hash.
  3. Import/install the package.
  4. Confirm expected skill discovery.
  5. Run one positive activation case.
  6. Run one unrelated negative activation case.
  7. Run a missing-tool honesty case.
  8. Test artifact/tool permissions when available.
  9. Preserve the transcript, permissions, failures, and result.