一键导入
curses
Discover the structural costs hidden in your strengths through behavioral dimension analysis, strength-shadow extraction, and attitude recommendations.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Discover the structural costs hidden in your strengths through behavioral dimension analysis, strength-shadow extraction, and attitude recommendations.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | curses |
| description | Discover the structural costs hidden in your strengths through behavioral dimension analysis, strength-shadow extraction, and attitude recommendations. |
Discover the structural costs hidden in your strengths.
Every strength casts a shadow. The shadow is not a flaw — it is the structural cost of a capability. Understanding the cost transforms a curse into a conscious trade-off.
Invoke this skill when:
Skip when:
| Phase | What | Mode |
|---|---|---|
| 1. Collect | Gather behavioral data | dimension-profiler agent |
| 2. Analyze | Strength-Shadow extraction | AI + user dialogue |
| 3. Recommend | Attitude principles + practice matrix | AI proposes |
| 4. Report | Generate HTML report | Automated |
If the user provides a specific question (e.g., "What are my curses?"), orient the analysis toward that question.
Same-session reuse: If dimension-profiler output is already available in this
conversation (from a prior /sophia or /curses run), skip Phase 1 entirely and
reuse that output. Both skills produce identical profiler results.
Two-step delegation (same pipeline as /sophia):
Step 1: Run coverage-scanner agent (see agents/coverage-scanner.md) to get
pre-aggregated session data (protocol counts, friction, session types, tools).
Step 2: Pass coverage output to dimension-profiler agent (see agents/dimension-profiler.md):
Analyze this user's behavioral dimensions from their session data.
coverage_data: [paste coverage-scanner output here]
data_sources:
rules_dir: ~/.claude/rules/
claude_md: ~/.claude/CLAUDE.md
settings_json: ~/.claude/settings.json
data_context: session-enriched
Return the dimension profile table with scores, confidence, and raw signals.
When coverage_data is provided, omit sample_size — the profiler derives
dimensions from aggregate data and does not sample raw files.
If a dimension's confidence is "low", include it in the analysis but mark it as provisional and note this in the report.
From the dimension profile, identify strengths and their structural costs.
For each dimension scoring above 65 (or below 35 — extremes in either direction):
These are heuristic starting points, not fixed outputs. Adapt based on actual data.
| Dimension extreme | Strength | Shadow |
|---|---|---|
| D2 high (Doubt) | Catches errors early | Verification depth becomes opportunity cost |
| D4 high (Systematic) | Consistent governance | Rule accumulation creates complexity |
| D5 high (UU) | Discovers new patterns | May defer KK maintenance |
| D6 high (Extended Mind) | Effective delegation | Curse activates on delegation failure |
| D1 high (Abductive) | Creative hypothesis | May skip systematic validation |
| D3 high (Dialogical) | Deep understanding | Extended exchanges consume time |
Look for patterns that emerge from dimension COMBINATIONS:
When presenting strength-shadow pairs, some combinations may be either a curse OR a deliberate strategy. In context-rich sessions, the user may have already articulated this distinction. In cold-start sessions, the AI must proactively surface both interpretations before the user validates.
Patterns that require dual-interpretation:
For these dual-interpretation patterns specifically, retain a Constitution gate before downstream derivation: "This pattern admits two readings — [strategy interpretation] or [curse interpretation]. Which better describes your experience?" The user's intent here is project-profile category (a) — user IS the measurement target — and cannot be auto-resolved regardless of profile; downstream recommendations depend on this choice. Single-interpretation pairs (e.g., D1+D2, isolated dimensions) bypass this gate and proceed via the relay path described under "User dialogue" below.
When presenting dimensions to the user, always include the human-readable explanation from the dimension-profiler output (e.g., "D4 Rule Orientation — how you govern work") so users unfamiliar with the framework understand what each dimension measures.
Present single-interpretation strength-shadow pairs (the majority — those without the dual-interpretation gate above) as text output and proceed directly to Phase 3 recommendations. End the Phase 2 output with a visible red-line discovery line so the correction pathway is explicit: "If any pair seems misclassified, say so — I'll re-derive from there." The user may red-line via free response at any subsequent turn — confirm, reframe, dismiss, or add context. Counter-evidence that changes the structural category triggers re-derivation of downstream recommendations on the next turn.
From validated strength-shadow pairs, derive:
Each principle addresses a specific shadow:
Principle N — [Title]
[2-3 sentence explanation of the principle and why it addresses this shadow]
Application:
[Concrete, actionable guidance for daily practice]
Rank by ROI — which principle would have the highest impact if adopted? Mark the highest-ROI principle explicitly.
Map principles to concrete situations:
| Situation | Principle | Action | Trigger |
|---|---|---|---|
| When X happens | Principle N | Do Y | Z condition |
Include 4-6 rows covering the most common situations.
Generate an HTML report following the cooperative's design system.
Read one of:
~/.claude/usage-data/report.html — extract CSSskills/report/references/html-template.md — use as template basisskills/curses/references/report-template.md — curses-specific componentsCheck the dimension-profiler's Data Context field:
Mark the report subtitle with the context tier (e.g., "708 sessions | data-only" or "708 sessions | session-enriched").
If the dimension profile and philosopher match are available from a prior
/sophia run in this session, include:
Save to ~/.claude/usage-data/curses-profile.html
Open in browser: open <filepath>
Work-unit triage for GitHub issues. Groups raw issues, fuses each group with the AGENTS.md northstar in session, and composes /distill to hand off each routed work unit.
Review markdown or HTML artifacts before fixation (publish/commit/deposit/merge) via /inquire × /sublate × /gap × /contextualize through a channel-first browser preview loop. Markdown renders via marked; HTML serves directly through a Shadow DOM. Each round mode is `apply + scan` (apply queued comments now + scan to surface findings into the next round's sidepanel) or `apply` (apply only). User-invoked via /comment-review.
Scoped empirical validation utility. Decomposes a target↔surrogate equivalence claim into verifiable facets, bounds a user-synchronized test space, captures evidence inside it, and carries the uncovered complement forward. Use when an inference-uncertain proposition (does it behave / perform / transfer / hold value) needs evidence in a smaller stand-in space, and you want the claim scoped to the conditions actually tested rather than asserted absolutely.
Convergence-paced code/PR review-resolve loop via /review-loop. Drives a pluggable review source (codex | code-review), passing it the design intent already captured for the changed surface (relevant project rules + adjacent design comments + decisions constituted at the loop's own gates, with a mission-anchored severity steer) so intentional documented choices are pre-filtered upstream, verifies each finding against the codebase (/inquire) and work-flow (/contextualize), auto-applies Mechanical fixes (Extension) and gates Judgment fixes by shared disposition (Constitution), risk-screens applies (substrate risk → harness permission; epistemic risk → direct Constitution), then re-reviews until the source verdict converges to approve — recurring signals escalate to constituted design decisions rather than suppression, keeping the reviewer independent. At exit, converged or free, a decision constituted at its gates is offered for durable record on the home its reach implies (for a PR scope, the issues the PR clo
Deficit Recognition Probe — surface multiple deficit hypotheses for the user's current situation and route by user-constituted recognition (fit review, not protocol scoring).
Distill a session-tethered working context into a self-contained portable handoff a fresh zero-memory agent can execute from. Closes deictic, grounding, relevance, provenance, and compression gaps, then emits a prose channel plus a schema-versioned TaskStateBlock. Type: (ContextTethered, AI, DISTILL, WorkingContext) → PortableHandoff. Alias: Diylisis(διύλισις).