CtrlK
BlogDocsLog inGet started
Tessl Logo

alfworld-environment-scanner

Performs an initial scan of the ALFWorld environment to identify all visible objects and receptacles. Use when you first enter an environment and need to build a mental map for task planning. Processes raw observation text into a structured list of entities, categorizing them as objects or receptacles.

66

Quality

83%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide
SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

81%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 tight, well-structured instruction skill with a clear numbered workflow, exact output format, and a worked example that leaves no ambiguity about what to do. The one real defect is that the bundled references/alfworld_actions_guide.md is orphaned — never referenced from the body — despite containing the action syntax and observation semantics the skill relies on.

Suggestions

Link the bundle reference from the body, e.g., under Execution Rules: 'For the full action set and observation semantics (e.g., \"Nothing happened.\" = invalid action), see [alfworld_actions_guide.md](references/alfworld_actions_guide.md)'.

Add a concrete rule for dual-category entities like `ottoman` (e.g., 'list dual-purpose entities under receptacles, since go to only accepts receptacle targets') to close the actionability gap.

Trim the 'Primary Objective' section, which restates the frontmatter description, and fold any needed framing into the workflow heading.

DimensionReasoningScore

Conciseness

The body is efficient — it never explains what ALFWorld is or how agents work, and every section carries operational content (trigger, parse rules, category definitions, output format, worked example). Minor trimmable padding remains, e.g., the 'Primary Objective' section restates the frontmatter description ('systematically identify and catalog all objects and receptacles'), which fits the level-4 'minor instances of over-explanation' anchor rather than the fully lean level 5.

4 / 5

Actionability

Guidance is concrete and executable: an exact output template ('Scan Complete. Receptacles: [list]. Objects: [list].'), a fully worked example with exact entity names, naming-convention details ('armchair 2', 'diningtable 1'), and the literal action 'go to sofa 1'. Per the rubric's instruction-skill note, absence of code is not penalized. It sits at level 4 rather than 5 because parsing edge cases are only gestured at ('Some entities (like `ottoman`) can be both depending on context') without concrete handling rules, a minor gap.

4 / 5

Workflow Clarity

The workflow is a clearly numbered sequence (Trigger → Parse & Extract → Categorize → Output Structured Mental Map) with unambiguous execution rules: exactly one 'go to' action, no looping, and explicit integration guidance for downstream planning. This is a simple single-purpose skill under 50 lines with no destructive or batch operations, so the simple-skill exception applies and the unambiguous single action merits 5; the anti-drift check confirms level 4's 'minor validation gaps' language does not fit better since no validation is needed here.

5 / 5

Progressive Disclosure

The body is short and cleanly sectioned (Core Workflow, Execution Rules, Example from Trajectory) with nothing inlined that belongs in a separate file. However, the bundle's one reference file — references/alfworld_actions_guide.md, which contains the observation semantics ('On the {recep}, you see...', 'Nothing happened.') this skill depends on — is never linked or mentioned, so navigation to the bundle is a clear miss. That matches level 4 ('good structure... minor organization gaps') rather than 5, whose anchor requires well-signaled one-level-deep references.

4 / 5

Total

17

/

20

Passed

Description

78%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: concrete third-person actions, an explicit 'Use when...' clause, and a well-scoped ALFWorld niche. The main room for improvement is making the trigger more vivid with the literal phrases the simulator emits and slightly broadening the natural-term coverage.

Suggestions

Add the literal simulator trigger phrasing to the 'when' clause, e.g., 'Use when you receive the initial observation (\"Looking quickly around you, you see...\") and need to map the room for task planning.'

Include common natural variations of the trigger terms, such as 'initial observation', 'look around', or 'scan the room', to broaden keyword coverage.

DimensionReasoningScore

Specificity

The description names several concrete actions — 'Performs an initial scan', 'identify all visible objects and receptacles', 'Processes raw observation text into a structured list of entities, categorizing them as objects or receptacles' — in third person, with only minor coverage gaps (e.g., the culminating `go to` action is unstated). This matches the 'several specific actions; minor gaps' anchor; it is not 5 because the action list stops short of full coverage of the skill's behavior, and not 3 because it goes well beyond 1-2 actions.

4 / 5

Completeness

Both halves are explicit: the 'what' ('Performs an initial scan... to identify all visible objects and receptacles... Processes raw observation text into a structured list') and the 'when' ('Use when you first enter an environment and need to build a mental map for task planning'). The 'when' clause is present but could be more concrete — e.g., quoting the actual initial-observation trigger — so it matches the level-4 anchor ('when' could be more explicit) rather than the fully concrete level-5 example, and clearly exceeds level 3 where 'when' is missing or only implied.

4 / 5

Trigger Term Quality

It includes good natural keywords — 'initial scan', 'first enter an environment', 'build a mental map', 'task planning', 'observation text' — that a user would plausibly say, though common variations like 'initial observation', 'look around', or the literal simulator phrasing ('Looking quickly around you') are missing. This fits the 'good keyword coverage; a few natural terms missing' anchor rather than the comprehensive-with-synonyms level 5, and is well above the sparse keyword levels 2-3.

4 / 5

Distinctiveness Conflict Risk

The 'ALFWorld environment' framing carves out a clear niche with a distinct situational trigger ('first enter an environment'), giving minimal conflict risk with any generic or non-ALFWorld skill, matching the level-5 anchor. It does not quite read as generic at level 3-4, since the domain and the scan-on-entry trigger are both specific.

5 / 5

Total

17

/

20

Passed

Validation

100%

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
Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.