alfworld-goal-interpreter

Parses the natural language task goal to extract actionable sub-objectives and required objects. Trigger this skill whenever a new task is assigned to break down complex instructions into clear, sequential targets. It interprets phrases like 'look at X under Y' to identify target objects (pillow), reference objects (desklamp), and spatial relationships (under).

Quality

73%

Does it follow best practices?

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Securityby

Passed

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Fix and improve this skill with Tessl

tessl review fix ./experiments/src/skills/alfworld/alfworld-goal-interpreter/SKILL.md

Quality

Content

62%

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

The content is well-structured with a clear sequenced workflow and feedback checkpoint, and it is concise. Its main weakness is referencing a `parse_goal.py` script that is not present in the bundle, which undermines both actionability and navigation.

Suggestions

Either add the referenced `parse_goal.py` to a scripts/ bundle or replace the script reference with the actual parsing logic (e.g., concrete regex/string steps) inline so the guidance is executable.

Confirm the `search_patterns.md` fallback reference resolves correctly and consider linking it with markdown syntax (e.g., [search_patterns.md](references/search_patterns.md)) so navigation is explicit.

Add a brief validation step after parsing (e.g., confirm primary_target, reference_object, spatial_relation, and action are all populated before generating sub-objectives) to harden the workflow.

Dimension	Reasoning	Score
Conciseness	The body is lean and assumes Claude's competence with no padding, but it directs Claude to a parsing script (`parse_goal.py`) that does not exist in the bundle, so some guidance is not actually usable — mostly efficient but includes a broken dependency.	2 / 3
Actionability	It gives structured, concrete-ish IF/relation rules and output schema, but the primary instruction hinges on a non-existent `parse_goal.py` and provides no executable code or commands, leaving key details missing as required for a 3.	2 / 3
Workflow Clarity	A clear four-step sequence (Parse → Generate Sub-Objectives → Identify Objects → Execute & Adapt) with an explicit monitoring/fallback checkpoint ('After each action, monitor the observation. If the expected object is not found... consult search_patterns.md'), matching the explicit-validation anchor.	3 / 3
Progressive Disclosure	Sections are well organized and `search_patterns.md` is a real one-level-deep reference, but `parse_goal.py` is referenced yet absent from the bundle, so navigation is partly broken rather than cleanly one-level-deep.	2 / 3
	Total	9 / 12 Passed

Description

85%

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 specific and answers both what and when with an explicit trigger clause, occupying a distinct niche. Trigger-term quality is the weakest dimension because the natural-language cues are domain-specific jargon rather than widely natural phrasings.

Dimension	Reasoning	Score
Specificity	Lists several concrete actions — 'Parses the natural language task goal to extract actionable sub-objectives and required objects' and 'interprets phrases like' — naming primary/reference objects and spatial relations, matching the 'multiple specific concrete actions' anchor.	3 / 3
Completeness	Explicitly answers what ('Parses the natural language task goal to extract actionable sub-objectives and required objects') and when ('Trigger this skill whenever a new task is assigned to break down complex instructions'), matching the 'clearly answers both what AND when' anchor.	3 / 3
Trigger Term Quality	Trigger guidance leans on domain jargon ('look at X under Y', 'pillow', 'desklamp', 'under') rather than broadly natural user keywords; some relevant terms but missing common variations, matching the 'some relevant keywords but missing common variations' anchor.	2 / 3
Distinctiveness Conflict Risk	Targets a clear niche (ALFWorld goal interpretation) with a distinct new-task trigger unlikely to fire for unrelated skills, matching the 'clear niche with distinct triggers' anchor.	3 / 3
	Total	11 / 12 Passed

Validation

100%

Warnings & errors only

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: zjunlp/SkillNet
Path: experiments/src/skills/alfworld/alfworld-goal-interpreter/SKILL.md
Commit: 7bb9a48

Reviewed: 1 day ago

Table of Contents

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