Content
88%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A tightly written orchestrator skill with an exemplary workflow structure — explicit sequencing, blocking checkpoints, a verify/retry loop, and clear stop conditions. The weaknesses are local rather than structural: a non-executable code snippet (missing import), a compose snippet whose top-level volumes key would be misplaced when appended, and an internal contradiction about whether to include the openai dependency.
Suggestions
Fix the embedder factory snippet by adding "import os" so it is copy-paste executable, and show the top-level "volumes:" key being appended at file scope (not inside services:) so the compose merge is unambiguous.
Resolve the dependency contradiction in step 3b item 6: it says "Do NOT add oci-openai or openai" while the always-list includes "openai>=1.40" — clarify which package is forbidden (presumably the oci-openai compat shim).
Verify the referenced bundle files (shared/references/*, shared/snippets/*, shared/templates/*, skills/*) ship alongside this SKILL.md, since roughly a dozen load-bearing paths are cited and none are present in this bundle.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense, imperative instruction end to end — exact env vars ("OCI_GENAI_API_KEY"), exact model ids ("xai.grok-4 (full id required — grok-4 alone won't resolve)"), a variable-resolution table, a line budget ("Don't write more than ~450 lines"), and a hard "What you must NOT do" list. No concept explanations Claude would already know; even the parentheticals ("do not add the legacy /20231130/actions/openai path — that is for SigV1, not bearer-token") are non-obvious domain specifics that earn their tokens. | 5 / 5 |
Actionability | Largely executable: a copy-paste docker-compose service block, a pinned dependency list ("fastapi>=0.110", "pypdf>=4"), a .env.example block, verify commands with expected output ("verify: OK (db, vector, inference)"), and curl-able endpoints. It falls short of fully copy-paste-ready: the embedder factory snippet uses os.environ without "import os", the "volumes: openwebui_data:" top-level key is shown appended inside the services block of the generated compose file, and item 6 contradicts itself — "Do NOT add oci-openai or openai" while the always-deps list already includes "openai>=1.40". | 4 / 5 |
Workflow Clarity | Steps 0–5 are explicitly ordered with rationale ("Order matters — invocation of building-block skills happens before project code"), blocking checkpoints ("Block until it reports OK"), a verification stage with expected output and an explicit recovery loop ("follow shared/verify.md recovery loop, max 3 retries"), a Stop conditions section, and a done-gate ("Don't claim done before verify is green AND the adapter boots cleanly"). Validation is present at every fragile point (DB health, dim == 384, /v1/models probe, port 3000 responds). | 5 / 5 |
Progressive Disclosure | Structure is good: a mandatory "Read these references first" section lists one-level-deep references with load-bearing markers ("langchain-oracledb.md ← load-bearing"), and inline content is limited to orchestration specifics rather than API reference. It is not a 5 because the referenced bundle files (shared/references/*, skills/*, shared/snippets/*) are not present alongside SKILL.md, so navigation and one-level depth cannot be verified, and some spec detail (dependency lists, .env.example contents, the final-report template) could live in a reference file to slim the overview further. | 4 / 5 |
Total | 18 / 20 Passed |