CtrlK
BlogDocsLog inGet started
Tessl Logo

research-ops

Evidence-first current-state research workflow for ECC. Use when the user wants fresh facts, comparisons, enrichment, or a recommendation built from current public evidence and any supplied local context.

68

Quality

83%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

SecuritybySnyk

Advisory

Suggest reviewing before use

SKILL.md
Quality
Evals
Security

Quality

Content

100%

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

The body is a tight, well-structured operator guide that assumes competence, gives concrete tool-by-tool escalation rules, sequences a five-step workflow with verification checkpoints, and stays cleanly sectioned with no reference-depth problems.

DimensionReasoningScore

Conciseness

The body is lean and dense, assumes Claude's competence (no explanation of what research or search is), and every section earns its place with no padding or verbosity.

3 / 3

Actionability

Gives concrete, executable guidance by naming specific skills with explicit escalation conditions ('use exa-search for fast discovery', 'escalate to deep-research when synthesis or multiple sources matter') plus a copy-ready output template, which is appropriately actionable for an instruction-only skill.

3 / 3

Workflow Clarity

A clearly numbered five-step sequence (Start -> Classify -> Evidence path -> Report -> Monitor) is backed by an explicit Verification section with checkpoints (labeled evidence types, dated freshness-sensitive output, mode-match confirmation).

3 / 3

Progressive Disclosure

No bundle files exist and content is organized into well-signaled sections (Skill Stack, When to Use, Guardrails, Workflow, Output Format, Pitfalls, Verification) with no nested reference chains; the inline output template is appropriately placed at one level.

3 / 3

Total

12

/

12

Passed

Description

67%

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 well-formed with an explicit Use-when clause and clear domain framing, but its action list is outcome-level rather than operation-level and it lacks the most common trigger phrasings, capping specificity and trigger_term_quality at 2.

Suggestions

Replace outcome categories with concrete operations the skill performs (e.g. 'compares options side-by-side', 'enriches people/company records', 'ranks decision options') to lift specificity toward 3.

Add the high-frequency natural trigger terms users actually say — 'research', 'look up', 'what's the latest' — directly into the description so trigger_term_quality covers common variations.

Sharpen distinctiveness by stating the coordinator role upfront (e.g. 'orchestrates exa-search, deep-research, and market-research') so it does not blur into the sibling skills it wraps.

DimensionReasoningScore

Specificity

Names the research domain and several outcomes ("fresh facts, comparisons, enrichment, or a recommendation") but these are output categories rather than the granular discrete operations (e.g. "extract text, fill forms, merge documents") the top anchor requires.

2 / 3

Completeness

Clearly states what it is ("Evidence-first current-state research workflow for ECC") and gives an explicit trigger clause ("Use when the user wants fresh facts, comparisons, enrichment, or a recommendation..."), satisfying both what and when.

3 / 3

Trigger Term Quality

Includes relevant natural terms ("fresh facts", "comparisons", "enrichment", "recommendation") but omits the most common user phrasings like "research", "look up", and "what's the latest" which appear only in the body, leaving gaps in common variations.

2 / 3

Distinctiveness Conflict Risk

The ECC scoping and evidence-first framing add some niche, but "research workflow" is broad and the skill itself coordinates sibling research skills (deep-research, exa-search, market-research), so it could still overlap with those similar skills.

2 / 3

Total

9

/

12

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.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository
affaan-m/ECC
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.