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obliteratus

OBLITERATUS: abliterate LLM refusals (diff-in-means).

60

Quality

75%

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SecuritybySnyk

Critical

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tessl review fix ./optional-skills/mlops/obliteratus/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

85%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.

The body is an actionable, well-sequenced operational guide with excellent command coverage, explicit verification thresholds, and strong error-recovery feedback loops. Its main weaknesses are bundle hygiene — broken templates/*.yaml references and an orphaned methods-guide.md — plus a few trimmable sections that dilute token efficiency.

Suggestions

Fix or remove the broken templates/abliteration-config.yaml, templates/analysis-study.yaml, and templates/batch-abliteration.yaml references — none of these files exist in the bundle.

Reference references/methods-guide.md from the body (e.g. from Step 4) so the detailed method guide is discoverable, and move the duplicated per-method detail out of SKILL.md into it.

Trim the 'Video Guide', 'What's inside', 'Complementary Skills', and 'Platform Support' sections and the duplicated AGPL warning (stated in both the intro and pitfall #10) to tighten token usage.

DimensionReasoningScore

Conciseness

The body is dominated by dense, useful tables and executable commands with little concept-explanation padding, matching the 'efficient; minor instances of over-explanation that could be trimmed' anchor. It is not 5 because of the 'Video Guide', 'What's inside' stats line, 'Complementary Skills', and 'Platform Support' sections plus the AGPL license warning stated twice (top and pitfall #10).

4 / 5

Actionability

Commands are copy-paste ready throughout: install checks, a runnable VRAM-detection script, full obliterate invocations with every flag documented, a complete flag table, verification metric thresholds, and downstream serving/upload commands. This matches the 'fully executable, covers the common cases' anchor.

5 / 5

Workflow Clarity

Steps 1-7 are clearly sequenced with a hardware checkpoint, method-selection guidance keyed to situations, and a verification step with explicit feedback loops ('If refusals persist...' and 'If coherence is damaged...' each giving concrete parameter adjustments). This matches the top anchor including error-recovery loops.

5 / 5

Progressive Disclosure

The overview links references/analysis-modules.md one level deep, but references/methods-guide.md exists in the bundle and is never referenced from SKILL.md (orphaned, undiscoverable), and the three templates/*.yaml paths cited in the body do not exist in the bundle. The inlined 9-method and direction-method details also duplicate methods-guide.md content that should be split out, matching the 'structure present but content that should be separate is inline / references not clearly signaled' anchor. It is not 4 because of the broken and orphaned bundle references.

3 / 5

Total

17

/

20

Passed

Description

57%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 highly distinct and technically specific, but it is a single terse fragment: it covers the 'what' adequately yet omits any 'when to use' trigger guidance and common synonyms like 'uncensor' or 'refusal removal'. Adding a 'Use when...' clause with natural trigger phrases would substantially raise completeness and trigger-term quality.

Suggestions

Add an explicit trigger clause, e.g. 'Use when the user wants to uncensor or abliterate an LLM, remove refusal/guardrail behaviors, or analyze how a model refuses.'

Include common synonyms users actually say — 'uncensor', 'refusal removal', 'weight projection', and example model families (Llama, Qwen, Mistral) — to broaden trigger-term coverage.

Mention one more concrete capability (e.g. verification metrics or steering-vector reversible alternative) to lift specificity beyond a single action.

DimensionReasoningScore

Specificity

The description names the domain ("LLM refusals") and one concrete action ("abliterate") with a specific technique ("diff-in-means"), matching the 'names domain and 1-2 concrete actions' anchor. It is not score 2 because the action is concrete rather than generic, and not score 4 because only one capability is listed with no coverage breadth.

3 / 5

Completeness

The 'what' is clear (abliterate LLM refusals via diff-in-means) but there is no 'Use when...' clause or equivalent trigger guidance, which per the judging guidelines caps completeness at 3. It is not score 2 because the 'what' is specific, not vague.

3 / 5

Trigger Term Quality

"abliterate" and "refusals" are terms users would naturally say, but common synonyms like "uncensor", "guardrails", or "refusal removal" (which the body's When-to-Use section itself lists) are missing from the description. This matches the 'some relevant keywords but missing common variations or synonyms' anchor.

3 / 5

Distinctiveness Conflict Risk

"abliterate LLM refusals (diff-in-means)" occupies a clear niche with distinct trigger terms and virtually no overlap risk with other skills, matching the top anchor.

5 / 5

Total

14

/

20

Passed

Validation

81%

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

Validation — 13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

metadata_field

'metadata' should map string keys to string values

Warning

frontmatter_unknown_keys

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

Warning

Total

13

/

16

Passed

Repository

NousResearch/hermes-agent

Path

optional-skills/mlops/obliteratus/SKILL.md

Reviewed

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