beam-ai-team/workable-master
skills/integrations/workable/workable-master/SKILL.md
All Workable ATS operations — fetch JDs, search candidates, post assessments/reviews. Load when user says "fetch JD", "search workable", "push to workable", "post review", "rate candidate", "workable", "push assessment", "list jobs", or after interview-coach completes an evaluation. Replaces workable-fetch-jd and workable-push-assessment.
tools
Updated Jul 3, 2026
$ install --global
skillsauthnpx skillsauth add beam-ai-team/beam-next-skills workable-masterInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- workable-master
- type:
- skill
- version:
- 2.0
- description:
- All Workable ATS operations — fetch JDs, search candidates, post assessments/reviews.
- author:
- Jonas Diezun
- category:
- integrations
- platform:
- Workable
- updated:
- 2026-02-16
- visibility:
- public
Workable Master
Single skill for all Workable ATS operations — JDs, candidates, assessments, and reviews.
When to use: Any Workable interaction — fetching JDs before interviews, searching candidates, posting assessments/reviews after evaluation.
Prerequisites:
WORKABLE_API_KEYin.envWORKABLE_SUBDOMAINin.envOutput: JD data, candidate info, or confirmation of posted assessment/review
Setup (One-Time)
Add these to your .env file:
WORKABLE_API_KEY=<workable-api-key>
WORKABLE_SUBDOMAIN=<workable-subdomain>
Get your API key: Workable → Settings → Integrations → Apps → Generate API token
Your subdomain: The part before .workable.com (e.g., joinbeam)
Operations
1. Fetch Job Description
# By title search
python3 03-skills/workable-master/scripts/workable_client.py --fetch-jd "Product Manager"
# By shortcode
python3 03-skills/workable-master/scripts/workable_client.py --fetch-jd-code 435CFC6C38
# JSON output (for programmatic use)
python3 03-skills/workable-master/scripts/workable_client.py --fetch-jd "Product Manager" --json
Returns: title, department, location, full description, requirements, benefits.
2. Search Candidates
# Global search
python3 03-skills/workable-master/scripts/workable_client.py --search "Sarah"
# Within a specific job
python3 03-skills/workable-master/scripts/workable_client.py --find-candidate-in-job 435CFC6C38 --candidate "Sarah"
3. Post Assessment (Comment)
# By name
python3 03-skills/workable-master/scripts/workable_client.py \
--candidate "Sarah Chen" --assessment "Assessment text..."
# From file
python3 03-skills/workable-master/scripts/workable_client.py \
--candidate "Sarah Chen" --file path/to/assessment.md
# By candidate ID
python3 03-skills/workable-master/scripts/workable_client.py \
--candidate-id abc123 --assessment "Assessment text..."
4. Post Review (Formal Evaluation with Grade)
python3 03-skills/workable-master/scripts/workable_client.py \
--candidate "Sarah Chen" \
--review --grade 2 \
--assessment "Full review text..."
Grade scale: 0 = No (thumbs down), 1 = Maybe (neutral), 2 = Yes (thumbs up)
Note: Only one review per member per candidate stage is allowed. Delete existing reviews from the Workable UI before re-posting.
5. List Open Jobs
python3 03-skills/workable-master/scripts/workable_client.py --list-jobs
Review Template (Standard Output)
After an interview evaluation, the review pushed to Workable should follow this template. This is the standard format for all candidate reviews.
Structure
CEO Interview Assessment — [Candidate Name] ([Role])
Date: [Date] | Stage: [Stage] | Duration: ~[X] min
━━━ EXPERT PANEL ASSESSMENT ━━━
[Expert 1 Name] ([Domain]) — X/10
• Strong: [observation with evidence]
• Strong: [observation with evidence]
• Concern: [observation with evidence]
• Concern: [observation with evidence]
[Expert 2 Name] ([Domain]) — X/10
• Strong: [observation with evidence]
• Strong: [observation with evidence]
• Concern: [observation with evidence]
• Concern: [observation with evidence]
[Expert 3 Name] ([Domain]) — X/10
• Strong: [observation with evidence]
• Strong: [observation with evidence]
• Concern: [observation with evidence]
• Concern: [observation with evidence]
━━━ BARREL SCORING (Keith Rabois Framework) ━━━
• Ownership Language (25%): X/10
• Specificity (25%): X/10
• Failure Stories (15%): X/10 — [brief note]
• Speed Instinct (20%): X/10 — [brief note]
• Hard Decisions (15%): X/10 — [brief note]
BARREL SCORE: X.X/10 → [BARREL / POTENTIAL BARREL / AMMUNITION / PASS]
[1-2 sentence barrel summary — what type of operator is this person?]
━━━ CANDIDATE SCORECARD ━━━
• Role-Specific Expertise: X/10 — [what was assessed: e.g. product thinking, sales methodology, ops systems]
• Execution Track Record: X/10
• Problem Solving: X/10
• AI Nativeness: X/10 — [how deeply do they use/build with AI today?]
• Communication: X/10
• Leadership / People: X/10
• Cultural Fit: X/10
Overall: X.X/10
━━━ INTERVIEW QUALITY ━━━
• Questions matched JD: [Yes/Partially/No] — [brief note]
• Failure probing: [Strong/Adequate/Weak] — [brief note]
• Case question quality: [Strong/Adequate/Weak] — [brief note]
• Time management: [Good/Okay/Poor] — [brief note]
━━━ RECOMMENDATION ━━━
[STRONG YES / YES / PROCEED WITH CAUTION / NO]
[2-4 sentence recommendation with clear next steps and comparison context.]
Expert Selection by Role
The 3 experts are selected based on the role being hired for. Always include perspectives that cover: (a) domain expertise, (b) operational/scaling lens, (c) people/culture lens.
| Role Category | Expert 1 (Domain) | Expert 2 (Ops/Scaling) | Expert 3 (People/Culture) | |--------------|-------------------|----------------------|--------------------------| | Product | Marty Cagan | Shreyas Doshi | Claire Hughes Johnson | | Engineering | Will Larson | Camille Fournier | Keith Rabois | | Sales | Mark Roberge | Jacco van der Kooij | Claire Hughes Johnson | | Marketing | Emily Kramer | April Dunford | Seth Godin | | Operations | Keith Rabois | Frank Slootman | Andy Grove | | Design/UX | Julie Zhuo | Don Norman | Steve Jobs | | AI/ML | Andrew Ng | Andrej Karpathy | Cassie Kozyrkov | | Customer Success | Lincoln Murphy | Elena Verna | Claire Hughes Johnson | | Executive/C-Suite | Ben Horowitz | Keith Rabois | Claire Hughes Johnson | | SDR/BDR | Aaron Ross | Meka Asonye | Mark Roberge | | Finance | Charlie Munger | Ray Dalio | Warren Buffett | | General/Other | Keith Rabois | Claire Hughes Johnson | Andy Grove |
Override: If a specific domain expert is more relevant (e.g., hiring for a PLG role → swap in Elena Verna), adapt the panel. The table is a starting point, not a constraint.
Barrel scoring (Keith Rabois framework) is always included regardless of role — it evaluates the universal ability to ship independently.
Grading to Workable Rating
Map the expert consensus + barrel score to the Workable thumbs scale:
| Expert Consensus | Barrel Score | Workable Grade | Meaning |
|-----------------|-------------|---------------|---------|
| Majority "Strong Hire" or "Hire" | 7.0+ | 2 (Yes) | Advance — strong candidate |
| Mixed / "Lean Hire" | 5.0 - 6.9 | 1 (Maybe) | Needs more signal — next round or debrief |
| Majority "No Hire" or "Lean No" | Below 5.0 | 0 (No) | Do not advance |
End-to-End Workflow
User: "review my interview with Sarah"
→ AI fetches transcript (Amie or Fathom)
→ AI: "What role was this for?"
→ User: "Product Manager"
→ AI fetches JD: workable_client.py --fetch-jd "Product Manager"
→ AI selects expert panel: Marty Cagan, Shreyas Doshi, Claire Hughes Johnson
→ AI runs expert assessments + barrel scoring
→ AI generates review in standard template
→ AI: "Push this to Sarah's Workable profile? (Grade: Yes/Maybe/No)"
→ User: "yes"
→ AI runs: workable_client.py --candidate "Sarah" --review --grade 2 --assessment "..."
→ "Review posted to Sarah's Workable profile."
Triggers
| User Says | Action |
|-----------|--------|
| "fetch JD for [role]" | Run --fetch-jd |
| "search workable for [name]" | Run --search |
| "push to workable" | Post last evaluation as review |
| "push assessment to workable" | Post as comment |
| "post review for [name]" | Post as review with grade |
| "list jobs" / "open positions" | Run --list-jobs |
| After interview-coach completes | Offer to push automatically |
Integration
Connected skills:
| Skill | Relationship |
|-------|-------------|
| interview-coach | Produces evaluations → pushes via this skill |
| candidate-compare | Produces comparisons → pushes via this skill |
| Amie / Fathom skills | Provides transcripts for evaluation |
Replaces: workable-fetch-jd (never created), workable-push-assessment (merged)
Version: 2.0 | Created: 2026-02-16
Changelog:
- v2.0: Unified skill combining JD fetching, candidate search, assessments, and reviews. Added standard review template with expert panel selection, barrel scoring, and grading matrix.
- v1.0: Initial push assessment skill (as
workable-push-assessment)
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