Conciseness

The body is lean and telegraphic with zero concept explanations ('Read only the route the task needs. First identify the input path...'); every line carries non-obvious repo-specific knowledge ('New translator or builder sources go into the explicit FRONTEND_SRCS list in tests/CMakeLists.txt, or the test binary fails to link'). No over-explanation exists to trim, so the score-4 anchor does not apply.

Actionability

Guidance is concrete and executable throughout: exact env vars with values ('OV_GGUF_REQUIRE_ARCH_FIXTURES=1', 'INFERENCE_PRECISION_HINT=f32', 'OV_GGUF_Q4_K_ZP_F16=1'), named test suites to rerun ('GGUFArchitectureAccuracy, GGUFArchConversion and the mmproj suites'), and a specific script invocation ('generate them with gen_arch_fixtures.py --fetch'). For an instruction-only routing skill, this matches the score-5 anchor's 'specific examples cover the common cases' without the pseudocode gaps of score 3.

Workflow Clarity

A clear sequence (identify input path → route via task table → apply pitfall checklist → validate) with explicit validation checkpoints and feedback guards: 'Run ov_gguf_frontend_tests unfiltered before finishing: the op-coverage gate runs in teardown, so check the exit status', 'Check actual selected counts and skips', 'check memory before starting one', and 'Verify graph attributes, plugin/executor parameters and the linked, loaded CPU variants before repeating a sweep'. Validation is present, so the batch-operation cap at 3 does not apply.

Progressive Disclosure

The body is a pure overview: a task→doc routing table with well-signaled one-level-deep links, verified against the actual bundle — references/validation.md and references/build-runtime.md exist with matching anchors (#family-contract, #scenario-environments), and the scripts (runtime_identity.py, summarize_tests.py) are surfaced from those reference docs rather than orphaned. Navigation is easy and content is appropriately split, matching the score-5 anchor.

Specificity

Multiple concrete actions are enumerated — 'Develop and troubleshoot the OpenVINO GGUF frontend... and the llama.cpp ggml-openvino backend', 'checking whether a .gguf or mmproj model is supported', 'adding a vision/audio projector or ProjectorExtension', 'making a converted model stateful or GenAI/PagedAttention-ready' — with no vague filler, matching the comprehensive-coverage anchor rather than the score-4 anchor ('minor gaps in coverage') since develop, troubleshoot, extend, validate and boundary cases are all covered.

Completeness

The 'what' is explicit ('Develop and troubleshoot the OpenVINO GGUF frontend (src/frontends/gguf) and the llama.cpp ggml-openvino backend that uses it') and the 'when' is given as an explicit 'Use when...' clause with many concrete trigger scenarios, plus a negative boundary ('Not for general llama.cpp usage or unrelated build/CI failures'). It clearly matches the score-5 anchor; the score-4 anchor ('when' could be more explicit) does not apply.

Trigger Term Quality

Natural terms include file extensions and formats ('.gguf', 'mmproj'), user-facing failure phrases ('rejected as an unsupported architecture', 'gives garbage, drifting tokens', 'decode-only shape failure'), model family names users actually say (llama, qwen, gemma, phi, MoE), and even the verbatim error string 'Translation for operation type GGML_OP_* is not implemented' a user would paste. This exceeds the score-4 anchor, which expects only 'a few natural terms missing'.

Distinctiveness Conflict Risk

The niche is sharply defined — this exact frontend/backend pair and its internal extension points (arch_registry, DecoderBuilder, ArchitectureExtension, ProjectorExtension) — and the explicit exclusion 'Not for general llama.cpp usage or unrelated build/CI failures' prevents the most likely wrong-skill trigger. Minimal conflict risk, matching the score-5 'clear niche with distinct triggers' anchor.