Context Engineering Fundamentals

The skill is primarily conceptual and includes a local Python example; it has no credential access, network writes, destructive defaults, or apparent privilege overreach, supporting a relatively strong baseline. Points are deducted because the script reads caller-supplied paths, silently returns empty strings for missing files, and does not document sensitive-data handling, path isolation, user confirmation, or recovery. Attribution is limited to contributor metadata, and the publisher is unverified.

The SKILL.md, reference, and script are broadly self-consistent, and the script has no third-party dependency requirements. Points are deducted for thin static evidence and diagnosability issues: message truncation accounts for budgets and message overhead inconsistently, ContextBuilder may silently omit over-budget sections, file-load failures return empty strings, and no dedicated tests cover this skill's key paths. Under static calibration, the score cannot exceed 10.

Activation scenarios, non-operational boundaries, and routing to specialized skills are clearly stated. The material is platform-agnostic and the core script is locally oriented. Points are deducted because input/output contracts, compatibility ranges, and finer false-positive boundaries are not specified; Chinese examples and Chinese-environment validation are absent. The core function does not entirely depend on overseas services, so no major mainland-network deduction is warranted.

The documentation has progressive structure and includes frontmatter, activation guidance, routing, examples, gotchas, a reference file, script documentation, creation/update dates, author, version, and an MIT license. Points are deducted because there is no explicit maintainer, changelog, or update procedure; external research references lack concrete auditable citations; and installation and troubleshooting guidance are incomplete.

The skill provides a directly useful conceptual framework for context, attention, progressive disclosure, and signal density, plus a reusable context-management script. Points are deducted because it is primarily educational and the selected skill's practical correctness and comparative benefit are not execution-verified; the sample implementation's approximate tokenization, truncation behavior, and silent failures may require user revision. Under static calibration, the score cannot exceed 7.

The script, reference, and metadata are statically auditable, and the repository includes general CI, validation scripts, and some test evidence. Points are deducted because those checks mainly cover repository tooling or other examples rather than this skill's key paths, while the central attention and performance claims lack reproducible third-party evidence in the supplied material. Under static calibration, the score cannot exceed 5.