analyze-trajectory — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited analyze-trajectory (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
For a defined industry, analyze direction of travel: dual S-curve position, Three Horizons portfolio overlay on G3 sub-segments, discontinuities, Helmer Power Progression, and base/bear/bull scenarios. Output: trajectory.md.
The discipline: trajectory is not extrapolation. Linear continuation past an inflection is the most common failure mode. Every assessment must name the diagnostic signal, the timing window, and the swing variable that could falsify it.
Iron rules:
../_shared/provenance-tagging.md.Confirm: industry slug, geographic scope, 5-year horizon (or justified alternative), and G3 sub-segment source. Check working/market-sizing.md in the same industry folder. If present, extract the G3 sub-segment table for Step 3 consumption. If absent (standalone mode), ask the user to supply ≥3 named sub-segments OR run size-market first. Record the source in the output header ("G3 source: working/market-sizing.md" or "G3 source: user-supplied at intake").
Read references/s-curve-methodology.md. Produce TWO assessments:
Then explicitly state whether the two are SYNCHRONIZED or DESYNCHRONIZED, and what the desynchronization implies. (Example: autos market = late maturity, tech = EV/AV early growth → tech S-curve will reshape the market S-curve within 5yr.)
Read references/three-horizons.md. Classify each G3 sub-segment (from Step 1) into H1 / H2 / H3:
Universal-H1 classification fails the bar test (real industries always have at least one H2 or H3 sub-segment unless explicitly declining). State the implied portfolio resource allocation as a single sentence (e.g., "70/20/10 conventional; this industry warrants 60/30/10 because [reason]").
Read references/discontinuities-catalog.md. Identify ≥2 discontinuities across the three types (regulatory / technology / behavioral). For each:
If only one discontinuity is identifiable across all three types in a 5yr horizon for a real industry, the search was incomplete — return to the reference and re-scan.
Read references/power-progression.md. Using the lifecycle stage from Step 2, map each of Helmer's 7 Powers to one of four states:
Hand off the Power-availability table to assess-moat-sources (which assesses which Powers a specific firm can build). This skill establishes the menu of available Powers; assess-moat-sources selects from the menu.
Read references/scenario-methodology.md. Produce three 5-year scenarios with ≥3 named swing variables:
Each swing variable is named, independent, and falsifiable. Examples: "EU AI Act enforcement intensity (light vs strict)", "GPU $/hour ($0.50 vs $0.20 by 2028)", "ambient-scribe EHR-integration mandate (yes/no by 2027)". Generic "growth could be higher or lower" fails validation.
Conditional rigor: If working/market-sizing.md exists (orchestrator mode), scenarios MUST be quantitative — ≥3 dollar figures ($XB / $XM) AND ≥3 CAGR figures (X% CAGR) across base/bear/bull combined. Validator fails the output otherwise. In standalone mode (no sibling market-sizing.md), qualitative scenarios pass with a soft warning. See references/scenario-methodology.md "Quantitative rigor" section.
If working/market-sizing.md exists, check that the S-curve stage assessed in Step 2 is consistent with the aggregate growth rate sized. Examples: growth-stage classification with <3% CAGR is contradictory; maturity-stage classification with 25% CAGR is contradictory. Flag mismatches as Gate 2 issues. If market-sizing.md is not present, add "size-market reconciliation deferred — market-sizing.md not present."
next_skills YAML blockEnd the output with:
---
next_skills:
- assess-moat-sources # consumes the Power-availability menu from Step 5
- analyze-demand # if behavioral discontinuities flagged in Step 4
---At least one skill required. Omit analyze-demand if no behavioral discontinuity was flagged.
Run python scripts/validate_trajectory.py --output-path <path> — checks dual S-curve (both market AND tech assessed with named stages), ≥3 H1/H2/H3 classifications, ≥2 discontinuities with explicit year-range timing windows, Power Progression mapping (all 7 Powers covered), scenarios with ≥3 named swing variables, V/C/A/I tag coverage ≥6, next_skills: YAML block. Write to working/trajectory.md (orchestrator) or standalone/analyze-trajectory-YYYY-MM-DD.md (standalone).
HTML on request (standalone only): markdown is the default and the only format the validator and the orchestrator consume. If the user explicitly asks for an HTML version of a standalone run, then after validation passes, also render the output via the html-output skill and review it per ../_shared/output-conventions.md § "HTML deliverables and quality review". Never produce HTML automatically.
encoding='utf-8'.None yet — v1 (initial build 2026-05-18).
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~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.