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book-sft-pipeline

This skill should be used for book-to-SFT pipelines: ePub extraction, literary segmentation, author-voice dataset construction, style-transfer training, LoRA workflows, and model evaluation for voice replication.

64

Quality

80%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./examples/book-sft-pipeline/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

73%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.

A well-structured, highly actionable skill body with a clear six-phase pipeline, strong validation practices, and real bundle references. Its main weaknesses are a padded cross-skill integration section, some repetition between phase rules and the guidelines checklist, and one broken reference plus an orphaned script.

Suggestions

Remove or drastically shorten the 'Integration with Context Engineering Skills' section — it describes other skills rather than instructing this one.

Fix the broken './examples/gertrude-stein/' reference (the directory does not exist) and add a pointer to the existing scripts/pipeline_example.py.

Deduplicate guidance repeated between the phase sections ('ePub over PDF', '15+ templates', paragraph boundaries) and the final Guidelines checklist.

DimensionReasoningScore

Conciseness

The core pipeline content (phases 1-6) is dense and useful, but the ~60-line 'Integration with Context Engineering Skills' section is non-actionable cross-referencing of other skills, and phase rules ('Always source ePub over PDF', '15+ templates') are restated verbatim in the Guidelines list. Fits 'mostly efficient but includes some unnecessary explanation or could be tightened' rather than score 2 since the padding is confined to one section plus minor repetition.

3 / 5

Actionability

Every phase has concrete, mostly executable Python (segment(), build_examples(), Tinker forward_backward/optim_step calls) plus shell validation commands. Not 5 because llm_call() is undefined, chunk.id/batches are unbound, and the epub2 import is dubious; not 3 because the code is real, not pseudocode.

4 / 5

Workflow Clarity

Six phases are explicitly sequenced with an architecture diagram up front, Phase 6 provides explicit validation (modern scenario tests, grep originality check, AI detectors), 'Known Issues' gives symptom/cause/solution feedback loops, and the 8-item Guidelines section serves as a checklist. This matches the full anchor: clear sequence, validation steps, error recovery, and checklist.

5 / 5

Progressive Disclosure

References are clearly signaled, one level deep, described inline, and all three ./references/ files exist on disk. Not 5 because the './examples/gertrude-stein/' link is broken (directory absent from the bundle) and scripts/pipeline_example.py exists but is never referenced from SKILL.md.

4 / 5

Total

16

/

20

Passed

Description

80%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.

A strong description that names the domain, lists comprehensive concrete capabilities, and includes an explicit activation clause. It could be improved by adding user-style trigger phrases and natural synonyms (ebook, fine-tune) to sharpen when-to-fire behavior and reduce overlap with generic fine-tuning skills.

DimensionReasoningScore

Specificity

The description enumerates six concrete actions spanning the full pipeline: 'ePub extraction, literary segmentation, author-voice dataset construction, style-transfer training, LoRA workflows, and model evaluation for voice replication'. Comprehensive coverage of specific actions, matching the top anchor.

5 / 5

Completeness

It has both a clear 'what' (the six-capability list) and an explicit trigger ('This skill should be used for...'), so it is not capped at 3. Not 5 because the 'when' merely restates the domain ('for book-to-SFT pipelines') rather than giving concrete user-phrase triggers like 'when the user mentions X'.

4 / 5

Trigger Term Quality

Good natural keyword coverage ('ePub', 'LoRA', 'style-transfer', 'book-to-SFT'), but common user phrasings like 'fine-tune a model on a book', 'ebook', '.epub', and 'SFT dataset' as natural language are missing. Falls between 'good coverage, a few missing' and 'comprehensive with synonyms/extensions'.

4 / 5

Distinctiveness Conflict Risk

The literary/book-to-SFT niche is distinctive, but 'LoRA workflows', 'style-transfer training', and 'model evaluation' overlap with general fine-tuning and evaluation skills. Mostly distinct with minor overlap risk against closely related skills.

4 / 5

Total

17

/

20

Passed

Validation

87%

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

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

relative_links

Relative link issues: 1 missing

Warning

Total

14

/

16

Passed

Repository
muratcankoylan/Agent-Skills-for-Context-Engineering
Reviewed

Table of Contents

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