CtrlK
BlogDocsLog inGet started
Tessl Logo

lead-intelligence

AI-native lead intelligence and outreach pipeline. Replaces Apollo, Clay, and ZoomInfo with agent-powered signal scoring, mutual ranking, warm path discovery, source-derived voice modeling, and channel-specific outreach across email, LinkedIn, and X. Use when the user wants to find, qualify, and reach high-value contacts.

63

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/lead-intelligence/SKILL.md

The canonical home for this skill is tdg-personal/lead-intelligence

SKILL.md
Quality
Evals
Security

Quality

Content

65%

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

The body is highly actionable with concrete code, formulas, and per-channel rules, and the pipeline is clearly staged. It is held back by missing batch-outreach validation feedback loops and the absence of real, linked reference files for progressive disclosure.

Suggestions

Add an explicit validation/dry-run checkpoint to Stage 5 outreach before any send — e.g., have the user review drafts, then re-confirm — so the batch operation has a validate→fix→retry loop.

Move the per-stage detail (signal weighting, bridge math, channel rules) into one-level-deep reference files under references/ and link them with clear "See X.md" pointers, since no bundle files currently exist.

Tighten the repeated Goal/Avoid/Anti-Pattern lists in the outreach section to reduce token weight while preserving the concrete guidance.

DimensionReasoningScore

Conciseness

Mostly efficient operational guidance Claude does not already know (signal weights, bridge formula, channel rules), but the factor tables, anti-pattern list, and repeated qualification text could be tightened without losing clarity.

2 / 3

Actionability

Provides concrete, executable guidance — a runnable Exa/X search Python snippet, an explicit bridge-score formula, weighted factor tables, and per-channel rules with specific execution patterns.

3 / 3

Workflow Clarity

The five-stage pipeline is clearly sequenced and includes a do-not-send guardrail, but batch outreach (a potentially irreversible operation) lacks an explicit validate→fix→retry feedback loop, which caps workflow clarity at 2.

2 / 3

Progressive Disclosure

The single SKILL.md is well-sectioned and references an agents/ subdirectory and related skills, but no bundle files exist under references/scripts/assets and the agents/ directory is named in prose rather than as one-level-deep, clearly signaled file links.

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, complete, and distinctive with an explicit Use-when trigger and concrete capability list. Its main weakness is trigger-term coverage, which omits the natural phrases (leads, outreach list, warm intros) a user would actually say.

Suggestions

Add natural trigger phrases to the description, e.g. "Use when the user asks to find leads, build an outreach list, find warm intros, or rank prospects to reach."

DimensionReasoningScore

Specificity

Lists multiple concrete actions — "signal scoring, mutual ranking, warm path discovery, source-derived voice modeling, and channel-specific outreach across email, LinkedIn, and X" — rather than vague language, written in third person.

3 / 3

Completeness

Explicitly answers both what (the pipeline stages and capabilities) and when via a clear "Use when..." clause, satisfying the completeness anchor.

3 / 3

Trigger Term Quality

"Use when the user wants to find, qualify, and reach high-value contacts" supplies natural triggers, but misses common variations a user would say such as "find leads", "outreach list", or "warm intros" that the body itself enumerates.

2 / 3

Distinctiveness Conflict Risk

The "Replaces Apollo, Clay, and ZoomInfo" framing plus a specific lead-intelligence niche gives it clear distinctiveness with triggers unlikely to fire for unrelated skills.

3 / 3

Total

11

/

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.