Skills DirectorySkills Directory
SkillsLearnSecurityCategoriesDocsCommunityBlog
Sign InSubmit Skill
Skills Directory

Security-tested agent skills for Claude, coding agents, and AI workflows.

Directory

  • Browse Skills
  • All Skills A–Z
  • Claude Skills
  • Claude Code Skills
  • Agent Skills
  • Categories
  • Authors
  • Submit a Skill

Learn

  • Learn Hub
  • Install Claude Skills
  • Write SKILL.md
  • Skills vs MCP
  • Directories Compared

Security

  • Security
  • Methodology
  • Secure Claude Skills
  • Security Badges

Company

  • About
  • Community
  • Blog
  • API Docs
  • Advertise

2026 Skills Directory. All rights reserved.

ProTermsPrivacyRefunds
Back to skills

Dymos Trajectory

ASecurity

Use when setting up and assessing pseudospectral trajectory optimization with Dymos: plan optimal-control problems as phases with collocation nodes, check that phase setup includes initial-state and final bounds plus an objective, and verify convergence, state continuity across segments, and total delta-v against expected budgets for ascent or orbit-transfer trajectories. Flags under-resolved phases (fewer than 5 nodes), unconverged runs, and discontinuities at segment boundaries. Trigger: tr...

2 stars
0 votes
0 copies
0 views
Added 9/27/2026
ai-agentspythonrustnode

Works with

claude code

Security Analysis

A100/100

Scanned 9/27/2026

Install to Claude Code

$npx -y skills add ashfordeOU/aero-agent-skills --skill dymos-trajectory --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Dymos Trajectory?

Add the live security badge to your README — it updates automatically with every re-scan.

Security grade badge for Dymos Trajectory
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/ashfordeou-dymos-trajectory/badge)](https://www.skillsdirectory.com/skills/ashfordeou-dymos-trajectory)

More formats (shields.io, HTML) on the badges page.

Download with Pro
Files
SKILL.md
---
name: dymos-trajectory
description: "Use when setting up and assessing pseudospectral trajectory optimization with Dymos: plan optimal-control problems as phases with collocation nodes, check that phase setup includes initial-state and final bounds plus an objective, and verify convergence, state continuity across segments, and total delta-v against expected budgets for ascent or orbit-transfer trajectories. Flags under-resolved phases (fewer than 5 nodes), unconverged runs, and discontinuities at segment boundaries. Trigger: trajectory optimization, optimal control, dymos, pseudospectral, phase, convergence, collocation, launch ascent, bounds."
license: Apache-2.0
compliance: STANDARDS-REF
standards:
  - id: arp4754a
    reference-only: true
gated: false
domain: gnc-autonomy
pack: gnc-autonomy
compatibility: "agentskills.io SKILL.md; any SKILL.md host (Claude Code, Hermes, OpenClaw)"
metadata:
  domain: gnc-autonomy
  subdomain: optimal-control
  tags: [trajectory-optimization, optimal-control, dymos, pseudospectral, phase, convergence, collocation, launch-ascent, bounds]
  version: 0.1.0
  author: Aero Agent Skills
---

# Dymos Trajectory Optimization (gnc-autonomy/optimal-control/dymos-trajectory)

Use when the task is pseudospectral trajectory optimization with
Dymos: phase setup, convergence checks, and trajectory validation.

## Domain quick reference

- Dymos transcribes optimal-control problems into phases solved
  with pseudospectral collocation; each phase needs a node count,
  state bounds, and an objective.
- Minimum usable collocation node count in this contract: 5.
- A solved trajectory must converge within the iteration and
  tolerance limits (default max_iter 50, tol_limit 1e-4).
- State values must be continuous across segment boundaries.
- Total delta-v should match the expected budget within a
  tolerance (default 10%).

## Workflow

1. Define the phases: node count, initial- and final-state bounds,
   objective.
2. Check phase setup completeness with scripts/dymos_logic.py
   before solving.
3. Solve and check convergence (iterations, tolerance).
4. Verify state continuity at segment boundaries.
5. Compare total delta-v against the expected budget.

## Pitfalls

- Solving with under-resolved phases (fewer than 5 nodes) and
  trusting the result.
- Missing initial/final bounds or objective in the phase
  definition.
- Accepting a run that hit the iteration cap without tightening
  the mesh or scaling.
- Treating segment-boundary discontinuities as converged.

## Behavior contract (gate 3)

The phase-setup, convergence, continuity, and delta-v logic is
exercised by the gate 3 contract test: scripts/test_dymos.py against
scripts/dymos_logic.py (stdlib unittest, offline). Run:
python3 scripts/test_dymos.py

## Compliance

- ARP4754A is proprietary (SAE); name + paraphrase only per
  standards-map.yaml and brief 06 (revision note: ARP4754B
  supersedes; this skill keys to A, the certification-baseline
  revision).
- compliance: STANDARDS-REF, gated: false.

Attribution

ashfordeOUashfordeOU
View sourceMore from ashfordeOU →
SSkills DirectorySkills Directory

Know which skills are safe — weekly.

Best new skills + every skill we flagged as malicious. From the team that scanned 103,619.

Join free

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments (0)

No comments yet. Be the first to comment!

SSkills DirectorySkills Directory

Know which skills are safe — weekly.

Best new skills + every skill we flagged as malicious. From the team that scanned 103,619.

Join free

Related Skills

Caveman

Ultra-compressed communication mode that cuts output tokens while keeping technical accuracy. Levels: lite, full, ultra and the wenyan variants. Use for /caveman, "caveman mode", "talk like caveman", "be brief" or "less tokens".

1074701 votes

Hyperplan

Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...

694821 votes

Mcp Code Execution

Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.

3351 votes

catchup

Recovers the conversation and failed tool calls of a previous Codex, Claude Code, Antigravity, Cline, Copilot CLI, Cursor, DeepSeek Harness, Kimi, OpenCode, Pi Agent, or ZCode session. Use when the user says "catch up", "what did the last session do", "get me up to speed", "I switched agents", asks to recover/summarize a previous session before continuing, or asks to diagnose or report a catchup failure. Do NOT use for the current conversation, git history, or any non-agent log.

691 votes

math-skill

A comprehensive mathematical reasoning skill for AI assistants — handles arithmetic to research-level problems with rigorous step-by-step reasoning, systematic verification, and transparent uncertainty handling

381 votes
View all in ai-agents →