skills/academic-letter-architect/SKILL.md
Guides the creation of evidence-based academic recommendation letters, reference letters, and award nominations that combine concrete examples, meaningful comparisons, and genuine enthusiasm. Use when writing recommendation letters for students, postdocs, or colleagues, or when user mentions recommendation letter, reference, nomination, letter of support, endorsement, or needs help with strong advocacy and comparative statements.
npx skillsauth add lyndonkl/claude academic-letter-architectInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Related skills (use instead for):
career-document-architectscientific-email-polishinggrant-proposal-assistant1. Show, don't tell: Concrete examples beat adjectives
2. Comparisons give context: Readers need reference points
3. Enthusiasm is evidence: Tone conveys conviction
4. Address what matters: Match content to opportunity
Copy this checklist and track your progress:
Letter Architect Progress:
- [ ] Step 1: Gather context (candidate, opportunity, relationship)
- [ ] Step 2: Collect evidence (specific examples, achievements)
- [ ] Step 3: Draft opening (credibility, relationship, expectation)
- [ ] Step 4: Build body (evidence paragraphs, comparisons)
- [ ] Step 5: Craft closing (strong endorsement, availability)
- [ ] Step 6: Calibrate tone (enthusiasm level, superlatives)
- [ ] Step 7: Final polish (length, format, signature)
Step 1: Gather Context
Identify: Who is the candidate? What opportunity? Your relationship (advisor, collaborator, instructor)? How long have you known them? In what capacity? See resources/methodology.md for information checklist.
Step 2: Collect Evidence
List 3-5 specific examples demonstrating excellence: Research achievements, intellectual contributions, professional qualities, overcoming challenges. Quantify where possible. See resources/methodology.md for evidence types.
Step 3: Draft Opening
Establish your credibility (position, experience). State relationship to candidate (role, duration, context). Set expectation (strong recommendation signal). See resources/template.md for opening structure.
Step 4: Build Body
Structure evidence into 2-4 paragraphs covering different dimensions (research, intellect, character). Include comparative statements ("top 5%", "best I've seen"). Connect evidence to opportunity requirements. See resources/template.md for paragraph templates.
Step 5: Craft Closing
Provide unambiguous endorsement statement. Offer availability for follow-up. Include professional signature with title/contact. See resources/template.md for closing structure.
Step 6: Calibrate Tone
Ensure enthusiasm matches actual assessment. Check superlative use (too many dilutes impact). Verify letter reads as advocacy, not obligation. See resources/methodology.md for calibration guide.
Step 7: Final Polish
Check length (typically 1-2 pages). Ensure formal formatting. Verify all specific claims are accurate. Validate using resources/evaluators/rubric_academic_letter.json. Minimum standard: Average score ≥ 3.5.
Purpose: Establish credibility and relationship
Elements:
1. Your identity and position
2. How you know the candidate (role, context)
3. Duration of relationship
4. Capacity of observation (direct supervision, collaboration)
5. Clear statement of recommendation
Example: "I am writing to provide my strongest recommendation for Dr. Jane Smith for the position of Assistant Professor. As the Director of the Structural Biology Center at X University, I have had the privilege of working closely with Jane for the past four years, first as her postdoctoral mentor and subsequently as a research collaborator. During this time, I have observed her exceptional scientific abilities, intellectual creativity, and professional maturity firsthand."
Purpose: Provide evidence-based assessment
Paragraph 1: Research/Technical Excellence
Paragraph 2: Intellectual Contributions
Paragraph 3: Professional Qualities
Paragraph 4: Comparative Assessment
Purpose: Summarize and endorse
Elements:
1. Overall assessment statement
2. Specific recommendation (enthusiastic, unambiguous)
3. Prediction for future success
4. Offer of availability for follow-up
5. Professional sign-off
Example: "In summary, Jane is an outstanding scientist with exceptional research abilities, intellectual depth, and professional maturity. I give her my highest and most enthusiastic recommendation without reservation. She will make an excellent faculty member and I am confident she will develop an impactful, independent research program. Please do not hesitate to contact me if you require any additional information."
Highest ("absolutely top"):
Strong ("top tier"):
Moderate ("good but not stellar"):
Lukewarm (damaging):
Strong comparisons:
Weak comparisons (avoid):
| Vague (Weak) | Specific (Strong) | |--------------|-------------------| | "Productive researcher" | "Published 5 first-author papers including 2 in Nature journals" | | "Good communicator" | "Regularly invited to present at lab meetings and gave a talk at the Gordon Conference" | | "Works well with others" | "Mentored 3 undergraduate students, all of whom went to top graduate programs" | | "Technically skilled" | "Independently established our lab's CRISPR screening platform" |
Key requirements:
Truthfulness: Only write what you genuinely believe. Dishonest letters harm candidates and your reputation.
Evidence-based: Every claim should have a supporting example. "Smart" means nothing without evidence.
Appropriate comparison: Compare to relevant reference class (other postdocs, not all scientists ever).
Match content to opportunity: Emphasize research for academic jobs, practical skills for industry.
Candidate voice preservation: Reflect the candidate's actual achievements, not fabricated ones.
Cultural awareness: US letters are more superlative than other cultures. Calibrate appropriately.
Common pitfalls:
Key resources:
Letter length guidelines:
Information to gather from candidate:
Time estimates:
Inputs required:
Outputs produced:
development
--- name: zettel-note description: The note-writing discipline for this vault's evergreen knowledge graph, modeled on a Zettelkasten reading companion and governed by the vault conventions. Enforces declarative-claim titles, one claim per note (atomicity), own-words prose with no block quotes, the piped [[slug|Title]] link form, the labeled link-relationship vocabulary (Confirms/Contradicts/Extends/Context/Prerequisite/Builds-on/Applies/Example-of/Contrasts-with), 3-6 links per note, and search-
development
Plans between-round FIFA World Cup Fantasy transfers — budgets the round's free transfer(s), forces out players whose nation has been eliminated, chases fixture-swing drops, upgrades on value, and decides when a rebuild is large enough to fire the Wildcard instead of spending free transfers one at a time. Ranks candidate in/out pairs by EV gain over each player's remaining survival horizon (delta xEV weighted by progression_carry) MINUS transfer cost (a free transfer is cheap, a points hit is real, churning the squad for marginal swings is a critic flag), and tags forced/fixture/upgrade priority. Emits a `transfer-plan` signal. Use when called by wc-squad-architect (whose transfer work this skill is the engine for) and by the strategists in the populate stage when their candidate is transfer-adjacent rather than a full rebuild.
testing
Reads and updates the FIFA World Cup Fantasy tournament state machine (footballfantasy/context/tournament-state.md) — the temporal backbone tracking phase (pre-tournament → group MD1-3 → R32 → R16 → QF → SF → final), budget ($100m group / $105m knockouts), nation cap (3 group, loosening in knockouts), chips remaining, surviving nations, each owned player's elimination-risk horizon, and deadlines. Validates state on load (count/feasibility checks), applies phase transitions, and appends to the append-only state log (never silent overwrite). Use to load state at the start of a run and to commit state changes after the manager makes a move.
development
Validates and persists FIFA World Cup Fantasy signal files to signals/YYYY-MM-DD-<type>.md. Checks the required frontmatter (type, round, date, emitted_by, confidence, source_urls), range-checks declared numeric signals, confirms every factual claim carries a source URL or "manager-provided", rejects unknown signal types, and refuses to persist a signal that fails validation (logging the failure instead). Keeps the inter-agent signal layer auditable so downstream agents can trust what they read and never re-derive it. Use whenever an agent or skill writes a signal.