| name | sh-personal-development-panel |
| description | Multi-expert personal-development review with scoring gate — learnability, adoption, human-centeredness, and capability impact for talent/learning/AI-augmentation designs |
/sh:personal-development-panel — Expert Personal-Development Review Panel
Usage
/sh:personal-development-panel [specification_content|@file] [--mode discussion|critique|socratic] [--focus learnability|adoption|human-centeredness|capability] [--experts "name1,name2"] [--iterations N] [--verbose]
Verbosity
- Silent (default): No expert deliberations. Output only: score table, FIPD-classified findings list, and auto-fix diff. Saves ~60-80% output tokens.
- Verbose (
--verbose): Full expert deliberations, cross-expert dialogue, reasoning traces, and detailed per-expert analysis before scores and findings.
Silent mode still performs full internal analysis — quality is preserved, only the output is compressed.
Behavioral Flow
- Load Protocol: Read
/Users/jcords-macmini/projects/20_agentflow/experts/PANEL_PROTOCOL.md and apply its Grounding (non-code branch — every finding quotes the source section it rests on) and Refute Stage sections. Findings that misquote or cannot cite the source MUST NOT be reported.
- Load Panel Config: Read
/Users/jcords-macmini/projects/20_agentflow/experts/panels/personal-development-panel.yaml for panel definition, focus areas, auto-select rules, and scoring config (absolute path — relative paths fail when CWD is outside agentflow)
- Load Experts: Read expert files from
/Users/jcords-macmini/projects/20_agentflow/experts/individuals/ for each selected expert — these files contain the expert's domain, methodology, and critique focus
- Auto-Select Experts: Scan the specification content against panel YAML
auto-select keywords — add matching experts up to max-experts: 8 cap
- Pre-Scoring Checks (deterministic — do NOT delegate to LLM personas):
- Table reconciliation: If the spec contains 2+ tables with numeric values (competence counts, capability-spine size, role-slice membership, "≥ N" thresholds), extract every numeric claim and verify cross-section arithmetic before personas opine. Enumerate the items the count refers to in the other sections; assert the math reconciles. Flag any mismatch as a CRITICAL finding up front. Rationale: LLMs reliably hallucinate arithmetic consistency over freeform tables — personas reading personas will not catch it. This step is mechanical, executed by the panel runner, not by an expert voice.
- Analyze: Parse specification content, identify components, gaps, and quality issues
- Assemble Panel: Select experts based on
--focus area or use default-experts from panel YAML. --experts override replaces defaults entirely
- Conduct Review: Run analysis in the selected mode using each expert's distinct methodology
- Score: Rate the design across 4 dimensions (0-10 each), compute overall score
- Gate Check: Overall score must be >= 7.0 to pass. Below threshold = design needs rework
Expert Loading
Experts are defined as individual markdown files in /Users/jcords-macmini/projects/20_agentflow/experts/individuals/. Each file contains structured frontmatter with:
- Domain and specialization
- Methodology and frameworks
- Critique focus and typical questions
The panel YAML (/Users/jcords-macmini/projects/20_agentflow/experts/panels/personal-development-panel.yaml) defines:
- Which experts belong to which focus area
- Who leads each focus area
- Auto-select keyword rules for dynamic expert addition
- Scoring dimensions and pass threshold
Default Panel
The default roster (7 experts) reviews every design unless --focus or --experts narrows it:
| Expert | Lens | Method |
|---|
| Dave Ulrich | HR / talent architecture | competency models, HR-from-the-outside-in, receiver-defined value |
| Malcolm Knowles | adult learning (andragogy) | six andragogical principles |
| Jeff Hiatt | change management (individual) | Prosci ADKAR |
| Erik Brynjolfsson | AI enablement / future of work | task-based augment-vs-automate, the Turing Trap |
| Amy Edmondson | psychological safety / teaming | psychological safety, intelligent failure |
| Ravin Jesuthasan | skills-based organization | work deconstruction (jobs→tasks→skills→capabilities) |
| Josh Bersin | enterprise L&D + AI | capability academies, commercialization, maturity models |
Auto-select adds Stuart Russell (AI safety / control) when autonomy/agentic/alignment keywords appear, up to the max-experts: 8 cap.
Analysis Modes
Discussion Mode (--mode discussion)
Collaborative improvement through expert dialogue. Experts build upon each other's insights sequentially. Cross-expert validation and consensus building around critical improvements.
Critique Mode (--mode critique)
Systematic review with severity-classified issues (CRITICAL / MAJOR / MINOR). Each finding includes: expert attribution, specific recommendation, priority ranking, and quality impact estimate.
Socratic Mode (--mode socratic)
Learning-focused questioning to deepen understanding. Experts pose foundational questions about purpose, learners, assumptions, and alternatives. No direct answers — forces the author to think critically.
Focus Areas
- learnability: Adult-learning fit — why-now framing, learner agency, problem-centered design. Lead: Malcolm Knowles. Experts: Knowles, Ulrich
- adoption: Will real people adopt and sustain the behavior — ADKAR rungs and psychological safety. Lead: Jeff Hiatt. Experts: Hiatt, Edmondson
- human-centeredness: Trust, safety, augmentation-over-replacement. Lead: Amy Edmondson. Experts: Edmondson, Brynjolfsson
- capability: Capability spine integrity, work deconstruction, individual→org→value line of sight. Lead: Ravin Jesuthasan. Experts: Jesuthasan, Ulrich, Brynjolfsson, Bersin
Scoring Gate
4 dimensions, each scored 0-10:
| Dimension | Description | Owner(s) |
|---|
| Learnability | Adult-learning soundness — why-now framing, learner agency, builds on experience | Knowles |
| Adoption-Readiness | Individual adoption through ADKAR rungs + psychological safety; barrier point named, reinforcement sustains behavior | Hiatt, Edmondson |
| Human-Centeredness | Human stays central — trust over surveillance, augmentation over replacement (Turing Trap avoided) | Edmondson, Brynjolfsson |
| Capability-Impact | Capability spine integrity + line of sight from individual competence to organizational capability to receiver-defined value | Ulrich, Jesuthasan |
Pass threshold: overall score >= 7.0
Output includes per-dimension scores, overall score, critical issues, expert consensus points, and an improvement roadmap (immediate / short-term / long-term).
Output
Personal-development review document containing:
- Multi-expert analysis with distinct perspectives
- Per-dimension scores and overall quality score
- Pass/fail gate result
- Critical issues with severity and priority
- Consensus points and disagreements
- Priority-ranked improvement recommendations
AUTO-FIX, NOT SYNTHESIS-ONLY — this panel produces the analysis AND then applies fixes for every finding (high, medium, and low) automatically, per 00_Governance/CLAUDE.md §8 Panel Auto-Fix Policy. It never asks which findings to apply and never presents a menu: it fixes everything, then reports what changed. A below-gate score means fix the findings and re-run, not stop and ask.
Auto-Fix Policy
Fix ALL findings automatically — high, medium, and low severity. Do not ask which findings to fix. Do not present a menu or an a/b/c choice. Fix everything, then report what was changed. This overrides any softer "synthesis only" framing. Per 00_Governance/CLAUDE.md §8.
Output Contract (machine-readable verdict)
The quality gate (quality_gate.run_stage3_panel) consumes this panel via
claude -p and reads the score from stdout, not the exit code. Therefore
the final line of your output MUST be exactly one of:
PANEL-VERDICT: <overall_score>
PANEL-VERDICT: FAIL: <machine_reason>
<overall_score> is the numeric overall score (0–10, one decimal — e.g. 8.3).
The gate applies the pass threshold (default 7.0); do NOT pre-apply it — just
report the score you computed.- Use the
FAIL: <machine_reason> form only when no score could be produced
(structural failure) — snake_case naming the first blocker (e.g.
no_content, panel_config_missing, experts_unavailable).
- Emit the line literally, on its own line, as the last meaningful output.
Omitting it makes the gate fail-closed with
panel_no_verdict (inconclusive).
