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context-fundamentals

Context is the complete state available to a language model at inference time. It includes everything the model can attend to when generating responses: system instructions, tool definitions, retrieved documents, message history, and tool outputs.

Quality

51%

Does it follow best practices?

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tessl review fix ./skills/context-fundamentals/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

36%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This is a well-organized conceptual overview, but it reads as an educational article rather than an operational skill: it re-explains fundamentals Claude already knows, provides few executable steps, and keeps all detail inline with a dangling internal reference. It would benefit most from trimming known-concept explanations and moving deep-dive material into real reference files.

Suggestions

Cut the explanations of concepts Claude already knows (attention mechanics, position encoding interpolation, the human-memory analogy) and keep only the synthesized engineering guidance.

Move the 'Detailed Topics' sections (Anatomy of Context, attention mechanics) into actual reference files under references/ and link them clearly, instead of the unresolved 'Context Components Reference' pointer.

Convert the Practical Guidance and Guidelines sections into a sequenced, actionable workflow — e.g., a numbered design/debug procedure with concrete checkpoints for measuring context usage and triggering compaction.

DimensionReasoningScore

Conciseness

The body is noticeably verbose: it re-explains concepts Claude already knows (attention as n-squared relationships, position encoding interpolation, 'retrieval on demand mirrors human cognition'), repeats the frontmatter description verbatim in the opening paragraph, and restates the 'finite resource / attention budget' idea across the Core Concepts, Context Windows, and Context as Finite Resource sections. It is not score 1 because genuine synthesized guidance (compaction thresholds, attention-favored positions) is present.

2 / 5

Actionability

Concrete guidance exists — the two markdown examples, 'Implement compaction triggers at 70-80% utilization', and 'Place critical information at attention-favored positions' — but it is embedded in long conceptual prose, and much of the Practical Guidance section is non-executable direction like 'Monitor context usage during development' with no method given. This matches 'some concrete guidance but incomplete'; not 4 because no command, script, or procedure can be directly executed.

3 / 5

Workflow Clarity

There is no sequenced process at all: the Guidelines section is an unordered heuristic list, and the Practical Guidance section presents three parallel strategies rather than steps with checkpoints. This fits 'rough sequence present but many gaps / steps poorly defined' at best; not 3 because even the guidelines lack an implicit order or any checkpoint for verifying context health.

2 / 5

Progressive Disclosure

The body is well-sectioned with clear headers, but ~180 lines of detailed conceptual material (Anatomy of Context, attention mechanics) are inlined where a reference file would serve, and the sole internal reference ('Context Components Reference - Detailed technical reference') points to no actual file in the bundle, while external resources are unlinked prose ('Research on transformer attention mechanisms'). This matches 'some structure but references not clearly signaled / content that should be separate is inline'; not 2 because section headers and a references section do provide real navigational structure.

3 / 5

Total

10

/

20

Passed

Description

45%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is a textbook definition of LLM context rather than a statement of what the skill does or when to use it. It is precise and information-dense, but offers no capabilities, no 'Use when...' trigger guidance, and weak differentiation from sibling context skills.

Suggestions

Rewrite the description to state what the skill provides (e.g., 'Explains the components of LLM context and how to curate them...') instead of defining the concept of context.

Add an explicit 'Use when...' clause with natural trigger phrases users would say: 'context engineering', 'context window', 'token budget', 'prompt design', 'reducing token costs'.

Include trigger synonyms and concrete capability verbs (design, debug, optimize context usage) to distinguish this skill from related skills like context-degradation and context-optimization.

DimensionReasoningScore

Specificity

The description names the domain and enumerates concrete components ("system instructions, tool definitions, retrieved documents, message history, and tool outputs") but describes zero actions the skill performs. It fits 'names the domain but actions are minimal or generic' — it is not pure abstract fluff (so not 1), but unlike score 3+ anchors it lists no concrete capability at all.

2 / 5

Completeness

It gives a clear topical 'what' (a definition of LLM context) but contains no 'Use when...' clause or equivalent trigger guidance, which caps completeness at 3 per the judging guidelines. It is not 4 because the 'when' is entirely absent rather than merely implicit.

3 / 5

Trigger Term Quality

Relevant keywords like "context", "tool definitions", and "message history" appear, but the natural phrases a user would actually say when needing this skill — "context engineering", "context window", "token budget", "prompt" — are missing. Some relevant keywords without common variations matches the score 3 anchor; it is above score 2 because more than one or two generic terms are present.

3 / 5

Distinctiveness Conflict Risk

The description is specific to LLM context, but as a pure definition it would trigger alongside closely related skills in the same collection (context-degradation, context-optimization, tool-design) that the body itself names. It is somewhat specific yet overlaps with similar skills, matching the score 3 anchor; not 4 because the definition-only framing gives it no distinct trigger of its own.

3 / 5

Total

11

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

administrakt0r/AI-Agents-Safe-Coding-Skills

Path

skills/context-fundamentals/SKILL.md

Reviewed

Table of Contents

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