beam-ai-team/candidate-compare

Candidate Compare

Data-driven candidate selection based on interview performance.

When to use: After interviewing multiple candidates for the same role, compare them objectively

Prerequisites:

• fathom-fetch-meetings — Get interview transcripts
• workable-fetch-jd — Pull job description for evaluation criteria

Output: Ranked candidates with scores, strengths/gaps analysis, hiring recommendation

---

Workflow

Step 1: Parse Input

Expected format:

User: "compare Sarah, John, Ahmed for Product Manager"

Extract:

• Candidate names: ["Sarah", "John", "Ahmed"]
• Role: Product Manager

Alternative triggers:

• "select best candidate for [role]" → ask for names
• "who should we hire for [role]" → ask for names
• "rank candidates" → ask for role and names

Step 2: Fetch Job Description

python3 03-skills/workable-fetch-jd/scripts/fetch_jd.py --job "[role]"

Extract key requirements from JD:

• Required experience (years, type)
• Technical skills
• Soft skills
• Nice-to-haves

Step 3: Fetch Transcripts

For each candidate, search Fathom:

# Search for meetings containing candidate name
curl -s --request GET \
  --url 'https://api.fathom.ai/external/v1/meetings?include_summary=true&include_transcript=true' \
  --header 'X-Api-Key: {FATHOM_API_KEY}' \
  | jq '.items[] | select(.title | ascii_downcase | contains("{candidate_name}"))'

If multiple meetings found for a candidate, pick the most recent or ask user to select.

Fallback: If Fathom unavailable, ask user to paste transcripts.

Step 4: Evaluate Each Candidate

Score each candidate on JD requirements:

| Dimension | Weight | What to Look For | |-----------|--------|------------------| | Experience Match | 25% | Years, industry, relevant projects | | Technical Skills | 25% | Demonstrated competency in required skills | | Problem Solving | 20% | How they approached challenges, structured thinking | | Communication | 15% | Clarity, conciseness, ability to explain complex ideas | | Culture Fit | 15% | Values alignment, work style, collaboration signals |

Scoring: 1-5 scale per dimension

• 5: Exceeds requirements
• 4: Meets requirements strongly
• 3: Meets requirements adequately
• 2: Partially meets requirements
• 1: Does not meet requirements

Step 4b: Barrel vs Ammunition Classification (REQUIRED)

Alongside the JD-fit score, classify each candidate as BARREL / POTENTIAL BARREL / AMMUNITION / PASS using Keith Rabois's framework. This is a pattern match, not a checklist — fire the "barrel alarm" on operator type, not on score arithmetic.

The 7 indicators (look for evidence in transcripts, project stories, summaries):

| Indicator | Signal | Anti-signal | |-----------|--------|-------------| | Takes initiative | "I noticed X and built Y without waiting" | "I was assigned to..." | | Ships high-quality work | "We iterated until it shipped at 95% accuracy" | "We hit the deadline" | | Values speed | "Rough first version live in a week, then iterated" | "We spent months designing" | | Takes accountability | "I owned it — and when it failed, here's what I did" | "The team's deliverable was..." | | Seen as a resource | "Teammates came to me when X broke" | No peer-pull evidence | | Recruits & motivates others | "I convinced 3 engineers to..." | "I worked with my assigned team" | | Handles adversity | "Compliance blocked us so I rebuilt on-prem" | "We were waiting for approval" |

Barrel arc (strongest single signal): Can the candidate credibly narrate Understand → Ideate → Take initiative → Recruit others → Deliver results on a real project? If yes, that's a BARREL flag even if individual indicators are missing.

Ownership language test: Count "I shipped" / "I owned" / "I convinced" vs "we did" / "the team" / "I was asked." Heavy "we"-framing without specifics is an Ammunition tell.

Classification rules:

| Tag | Criteria | Recommendation override | |-----|----------|------------------------| | BARREL 🛢️ | Most indicators fire AND can narrate the full arc on a real project | "Close on sight" — hire even if JD-fit weak, find or shape a role (per Rabois) | | POTENTIAL BARREL | 3–4 indicators fire OR partial arc with strong single signals | Watch-list; might emerge with right environment + stretch | | AMMUNITION | High-quality execution within defined scope; doesn't pull others | Hire if JD-fit strong. Not a put-down — necessary, just bounded throughput | | PASS | Neither barrel signals nor quality execution signals | Decline |

Critical: If a candidate classifies as BARREL but JD-fit < 3.5/5, the final recommendation must surface the Rabois override: "Close them anyway — find or shape a role later." Do not soften this; it's the user's hiring philosophy.

Evidence-or-flag rule: If an indicator can't be assessed from available data, write "insufficient evidence" — don't score it 0. Barrel classification is qualitative, not arithmetic.

Step 5: Compare & Rank

Calculate weighted JD-fit score for each candidate:

JD Fit = (Experience × 0.25) + (Technical × 0.25) + (Problem Solving × 0.20) + (Communication × 0.15) + (Culture × 0.15)

Rank candidates by JD-fit score, but report the Barrel classification independently — it is not a tiebreaker, it is a separate decision dimension that can override the JD-fit rank (see BARREL override above).

---

Output Format

This is THE format. Do not deviate without explicit user instruction.

# Candidate Comparison: [Role]

## Summary

| Rank | Candidate | JD Fit | Barrel | Recommendation |
|------|-----------|--------|--------|----------------|
| 1 | [Name] | X.X/5 | [BARREL 🛢️ / POTENTIAL BARREL / Ammunition / Pass] | [verdict] |
| 2 | [Name] | X.X/5 | [classification] | [verdict] |

> **Override:** [Triggered — see Recommendation] OR [Not triggered. No candidate classifies as BARREL, so JD-fit rank stands.]

Always print the Override line, even when not triggered — it confirms the check ran.

---

## [Candidate Name] — JD Fit X.X/5 · [CLASSIFICATION]

> Header embeds classification inline. No separate "Detailed Analysis" wrapper section, no rank number prefix, no ⭐ — the rank lives in the Summary table.

**JD-Fit Scores:**
| Dimension | Score | Notes |
|-----------|-------|-------|
| Experience Match | /5 | [brief note] |
| Technical Skills | /5 | [brief note] |
| Problem Solving | /5 | [brief note] |
| Communication | /5 | [brief note] |
| Culture Fit | /5 | [brief note] |

**Barrel Assessment:**

| Indicator | Fired? | Evidence |
|-----------|--------|----------|
| Takes initiative | ✅ / ⚠️ / ❌ / — | "[quote or 1-line evidence; '—' = insufficient evidence, never score 0]" |
| Ships high-quality work | ✅ / ⚠️ / ❌ / — | "[evidence]" |
| Values speed | ✅ / ⚠️ / ❌ / — | "[evidence]" |
| Takes accountability | ✅ / ⚠️ / ❌ / — | "[evidence]" |
| Seen as a resource | ✅ / ⚠️ / ❌ / — | "[evidence]" |
| Recruits & motivates | ✅ / ⚠️ / ❌ / — | "[evidence]" |
| Handles adversity | ✅ / ⚠️ / ❌ / — | "[evidence]" |

**Barrel arc** (Understand → Ideate → Initiative → Recruit → Deliver): **[Yes / Partial / No]** — [1-sentence note on whether they can credibly narrate the full loop on a real project named in the transcript]

**Ownership language ratio:** [observation on "I shipped/owned/convinced" vs "we did / the team / I was assigned"]

**Why [CLASSIFICATION] not [next-tier-up or next-tier-down]:** [REQUIRED — 2–4 sentences explaining the classification boundary call. Name the structural tells, not just the indicator counts. This is the most important paragraph in the section.]

**Strengths:**
- [Strength 1 with evidence]
- [Strength 2 with evidence]

**Gaps/Risks:**
- [Gap 1 — and how to mitigate or what to probe in next round]

**Key Quote:**
> "[memorable quote from interview]"

---

## [Next Candidate Name] — JD Fit X.X/5 · [CLASSIFICATION]

[Same structure — repeat the full block per candidate]

---

## Recommendation

**Hire / Advance / Pass:** [Name(s) and decision]

**Rationale:** [2–3 sentences. MUST cite both JD-fit AND Barrel classification. If both candidates are non-Barrel, name the structural reason for the recommendation (e.g., service-vs-product mismatch, AI/ML gap), not just the score gap.]

**Barrel override:**
- If a candidate classifies as **BARREL** but ranks below on JD-fit, surface verbatim: *"[BARREL Name] ranked below [other] on JD-fit, but is a Barrel. Per Rabois, close them — find or shape a role. Do not let JD-fit alone make this call."*
- If no override triggers, write: *"No override. JD-fit rank stands."*

**Probing questions for next round** (if any candidate is POTENTIAL BARREL):
- [Specific question to test the missing arc step, e.g., "Walk me through a project you championed against resistance — original idea, who else you needed, what you'd do differently."]
- [Specific question to confirm or downgrade the classification]

**Next Steps:**
- [ ] [Action item 1]
- [ ] [Action item 2]

---

## Comparison Matrix (vs. JD)

| Requirement (from JD) | [Candidate 1] | [Candidate 2] | [Candidate 3] |
|-----------------------|---------------|---------------|---------------|
| [Req 1] | ✅ Strong | ⚠️ Partial | ❌ Gap |
| [Req 2] | ✅ Strong | ✅ Strong | ⚠️ Partial |
| [Req 3] | ⚠️ Partial | ✅ Strong | ✅ Strong |

---

## Notes (optional but recommended)

- Use this section for structural observations: interviewer consistency, transcript quality caveats, hypotheses about why disqualified candidates were rejected vs. what the screening surfaced, etc.
- Example: "Both screens by Rabia Zaki — interviewer consistency holds." or "Adeel's summary is ~50% longer than Hannan's — could reflect substance or just verbosity; don't over-weight."

---

Triggers

| User Says | Action | |-----------|--------| | "compare [name1], [name2], [name3] for [role]" | Full workflow | | "compare candidates for [role]" | Ask for candidate names | | "select best candidate" | Ask for role and names | | "who should we hire for [role]" | Ask for names | | "rank candidates for [role]" | Ask for names | | "best candidate for [role]" | Ask for names |

---

Integration

Connected skills: | Skill | Purpose | |-------|---------| | fathom-fetch-meetings | Get interview transcripts by candidate name | | workable-fetch-jd | Pull job requirements for evaluation criteria |

Example Flow:

Manager: "compare Sarah Chen, John Smith, Ahmed Hassan for Product Manager"
→ AI fetches Product Manager JD from Workable
→ AI searches Fathom for "Sarah Chen", "John Smith", "Ahmed Hassan"
→ AI evaluates each against JD requirements
→ AI outputs ranked comparison with recommendation

---

Edge Cases

| Scenario | Handling | |----------|----------| | Candidate not found in Fathom | Ask user to paste transcript or skip candidate | | Multiple meetings for same candidate | Use most recent, or ask user to select | | JD not found in Workable | Ask user to paste JD or describe role requirements | | Only 2 candidates | Run comparison with 2 | | Tie in scores | Break tie with qualitative analysis, highlight trade-offs |

---

Bias Mitigation

• Evaluate all candidates against the same criteria (JD requirements)
• Use specific evidence from transcripts, not impressions
• Flag when a dimension lacks data: "Insufficient evidence to score"
• Present trade-offs, not just a winner

---

Version: 1.2 | Created: 2026-02-06 | Updated: 2026-06-12

Changelog:

• v1.2: Hardcoded output format. Per-candidate header now embeds classification inline (## Name — JD Fit X.X/5 · CLASSIFICATION), no rank prefix or ⭐. Override line always printed under Summary (even when not triggered). Required "Why [CLASSIFICATION] not [next-tier]:" rationale paragraph per candidate. Probing-questions block in Recommendation when any candidate is POTENTIAL BARREL. Notes section for structural observations.
• v1.1: Added Barrel vs Ammunition classification (Keith Rabois framework) as a parallel decision dimension to JD-fit. 4-tier tag (BARREL / POTENTIAL BARREL / AMMUNITION / PASS), 7-indicator pattern match + Barrel-arc test, "close on sight" override when BARREL underperforms on JD-fit.
• v1.0: Initial creation — compare up to 5 candidates, weighted scoring, JD-based evaluation