agentleFS
QaliAIQaliAI/ai-job-agent/skills/find-consulting-opportunities/SKILL.md

find-consulting-opportunities

Skill0 starsChanged 3 months agoMITView on GitHub

Discover evidence-backed consulting, fractional, advisory, coaching, implementation, and buyer-signal opportunities that are not ordinary job postings.

The file

We split this skill into the rules it gives an agent

6 rules. About 0 are common, 4 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈4

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use this skill when the candidate wants revenue opportunities beyond conventional employment.

    line 10
  2. Distinctive:

    Every opportunity must include:

    line 27
  3. Distinctive:

    Never invent a person's name, title, email, phone number, budget, or business pain.

    line 35
  4. Very specific:

    Read candidate/MASTER_PROFILE.md, candidate/OPPORTUNITY_TRACKS.json, and candidate/SEARCH_PREFERENCES.md.

    line 39
  5. Distinctive:

    Search public sources for current evidence.

    line 40
  6. Very specific:

    Use the normalized target_person_roles as a research order, not as proof that a specific person is correct.

    line 48

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

find-consulting-opportunities

Use this skill when the candidate wants revenue opportunities beyond conventional employment.

Goal

Find organizations with a verifiable current signal that maps to one of the candidate's opportunity tracks, then produce a normalized research lead. Do not infer a need from industry stereotypes alone.

Good source signals

  • a company explicitly announcing an AI, automation, CRM, digital-transformation, or growth initiative;
  • a company posting several related implementation roles that indicate an active program;
  • a public request for an advisor, fractional executive, trainer, workshop leader, product builder, or automation implementer;
  • a project marketplace listing;
  • a company publicly describing a manual workflow, integration gap, lead-response problem, or growth-system problem;
  • a warm/referral signal provided by the user.

Required evidence

Every opportunity must include:

  • company or organization;
  • source and source URL when available;
  • dated/current evidence whenever possible;
  • the exact signal that makes the opportunity relevant;
  • the best matching candidate opportunity lane;
  • likely role categories that own the problem.

Never invent a person's name, title, email, phone number, budget, or business pain.

Workflow

  1. Read candidate/MASTER_PROFILE.md, candidate/OPPORTUNITY_TRACKS.json, and candidate/SEARCH_PREFERENCES.md.
  2. Search public sources for current evidence.
  3. Save raw research records using templates/CONSULTING_OPPORTUNITY_TEMPLATE.json as the contract.
  4. Normalize them with scripts/opportunity_model.py or equivalent tool invocation.
  5. Generate a brief with scripts/opportunity_brief.py.
  6. Present opportunities for human review before any contact or application.

Person targeting

Use the normalized target_person_roles as a research order, not as proof that a specific person is correct.

Examples:

  • AI transformation -> Chief AI Officer, CIO, CTO, COO, transformation leader.
  • AI product build -> CTO, VP Engineering, Head of Product, founder.
  • Growth / CRM / automation -> CMO, CRO, VP Growth, RevOps leader, founder.
  • Fractional advisory -> founder/CEO, president, COO, operating partner.
  • Coworking / PropTech -> owner, CEO, COO, CMO, VP Sales.

Outreach boundary

The skill may prepare a factual draft after the user selects a lead. It must not mass-send messages or fabricate personalization.

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