CtrlK
BlogDocsLog inGet started
Tessl Logo
SkillPublic

apify-market-research

Analyze market conditions, geographic opportunities, pricing, consumer behavior, and product validation across Google Maps, Facebook, Instagram, Booking.com, and TripAdvisor.

Quality

75%

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

Fix and improve this skill with Tessl

tessl review fix ./skills/apify-market-research/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

75%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, actionable skill body with a clear five-step workflow, a useful Actor-selection table, executable commands, and unusually good cost/safety guardrails (billing warnings, retry guidance, privacy limits). The main gaps are cosmetic-to-minor: a missing worked example with a real input payload, an unverifiable script reference, a generic Limitations section, and a run-on Run Boundaries paragraph.

Suggestions

Add one fully worked example: a concrete Actor ID from the table paired with a realistic JSON_INPUT and its command line, making the Step 4 guidance copy-paste ready.

Restructure the "Run Boundaries" paragraph into a bullet list and trim the generic "Limitations" boilerplate to skill-specific statements.

Resolve or verify the referenced runner script path (reference/scripts/run_actor.js) so the single external reference points at a real bundle file.

DimensionReasoningScore

Conciseness

The body is almost entirely tables, checklists, and ready-to-run commands with no padding explaining known concepts. Minor trimmable spots keep it below anchor 5: the three Step 4 bash blocks differ only in --output/--format lines, the "Limitations" section is generic boilerplate, and "Run Boundaries" is one dense 10-sentence paragraph that should be a bullet list.

4 / 5

Actionability

Commands are complete and executable for all three output modes, the Actor table gives 16 real Actor IDs, and error strings map to specific recovery actions (e.g. "Inspect the printed run ID in Console before retrying to avoid duplicate charges"). Below anchor 5 because ACTOR_ID/JSON_INPUT placeholders are never instantiated — no worked example with a real Actor ID and a sample input JSON — and the referenced run_actor.js is not present in the bundle.

4 / 5

Workflow Clarity

Five sequenced steps with a copy-track checklist, pre-run checkpoints (prerequisites verified "before any paid run", schema fetched in Step 2 before the paid Step 4 run), and an error-to-action feedback loop in Error Handling. The batch/paid cap does not apply since validation checkpoints exist. Below anchor 5 because no explicit output-verification step precedes the Step 5 report (file existence/content check is implicit).

4 / 5

Progressive Disclosure

The ~120-line body is well-sectioned with the Actor table and commands appropriately inline and the single external reference (the runner script) clearly signaled in the command paths. Below anchor 5 because the referenced "<resolved-skill-directory>/reference/scripts/run_actor.js" cannot be verified against the bundle (no references/ or scripts/ files are present), so navigation to the core executable artifact is unconfirmed.

4 / 5

Total

16

/

20

Passed

Description

66%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 specific, platform-anchored description that clearly states what the skill does, but it completely lacks a "Use when..." trigger clause, which caps completeness at 3 and weakens its value for skill selection. Adding explicit trigger guidance and a few common synonyms (market research, competitor analysis) would lift it toward the top anchors.

Suggestions

Append an explicit trigger clause, e.g. "Use when the user needs market research, competitor or pricing analysis, or regional demand data sourced from Google Maps, Facebook, Instagram, Booking.com, or TripAdvisor."

Include natural synonyms users actually say — "market research", "competitor analysis", "demand", "trends" — to broaden trigger-term coverage.

Vary the verbs beyond "Analyze" (e.g. "extract", "compare", "validate") to move from one action with five objects toward multiple distinct concrete actions.

DimensionReasoningScore

Specificity

The description names five concrete analysis targets ("market conditions, geographic opportunities, pricing, consumer behavior, and product validation") across five enumerated platforms. It falls short of anchor 5 because it uses a single verb ("Analyze") with multiple objects rather than multiple distinct concrete actions like the 5-anchor examples (extract, fill, merge, convert).

4 / 5

Completeness

The "what" is clear (analyze market conditions, pricing, consumer behavior, and product validation across named platforms), but there is no "Use when..." clause or equivalent explicit trigger guidance, which the rubric guidelines cap at 3. The "when" is entirely absent, not merely weakly implied.

3 / 5

Trigger Term Quality

Natural phrases users would say are present ("market conditions", "pricing", "consumer behavior", "product validation", plus Google Maps, Facebook, Instagram, Booking.com, TripAdvisor). It misses common variations such as "market research", "competitor analysis", "demand", and "trends", keeping it below anchor 5's synonym-level coverage but well above anchor 3.

4 / 5

Distinctiveness Conflict Risk

The enumerated platform list (Google Maps, Facebook, Instagram, Booking.com, TripAdvisor) carves out a mostly distinct niche versus generic research or document skills. Minor overlap risk remains with other market-analysis or web-scraping skills since no explicit trigger phrases distinguish it, keeping it below anchor 5.

4 / 5

Total

15

/

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

sickn33/agentic-awesome-skills

Path

skills/apify-market-research/SKILL.md

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.