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

E1004 Ref Plasma

ASecurity

Use when determine the ECSS-E-ST-10-04C Annex H plasma-environment reference region for a mission orbit regime (ionosphere, plasmasphere, auroral, outer magnetosphere, solar wind, magnetosheath, magnetotail/L2), validate a candidate density or temperature value against that region's reference order-of-magnitude range, derive a log-space representative value for margin analysis, and identify the hot, tenuous plasma condition associated with spacecraft surface-charging risk. Trigger: ecss, e-st...

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

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 e1004-ref-plasma --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of E1004 Ref Plasma?

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

Security grade badge for E1004 Ref Plasma
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/ashfordeou-e1004-ref-plasma/badge)](https://www.skillsdirectory.com/skills/ashfordeou-e1004-ref-plasma)

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

Download with Pro
Files
SKILL.md
---
name: e1004-ref-plasma
description: "Use when determine the ECSS-E-ST-10-04C Annex H plasma-environment reference region for a mission orbit regime (ionosphere, plasmasphere, auroral, outer magnetosphere, solar wind, magnetosheath, magnetotail/L2), validate a candidate density or temperature value against that region's reference order-of-magnitude range, derive a log-space representative value for margin analysis, and identify the hot, tenuous plasma condition associated with spacecraft surface-charging risk. Trigger: ecss, e-st-10-04c, annex h, plasma environment, plasma density, plasma temperature, ionosphere, plasmasphere, auroral, magnetosphere, solar wind, magnetosheath, magnetotail, spacecraft charging."
license: Apache-2.0
compliance: STANDARDS-REF
standards:
  - id: ecss
    reference-only: true
gated: false
domain: space-systems
pack: space-systems
compatibility: "agentskills.io SKILL.md; any SKILL.md host (Claude Code, Hermes, OpenClaw)"
metadata:
  domain: space-systems
  subdomain: ecss
  tags: [ecss, e-st-10-04c, plasma, plasma-environment, ionosphere, plasmasphere, magnetosphere, spacecraft-charging]
  version: 0.1.0
  author: Aero Agent Skills
---

# ECSS Space Environment — Plasma Region Reference Data (space-systems/ecss/e1004-ref-plasma)

Use when the task needs an order-of-magnitude plasma density and
temperature reference for a spacecraft's orbit regime under
ECSS-E-ST-10-04C Annex H (info) -- selecting the applicable reference
region, checking a candidate value against that region's range, and
screening for the hot, tenuous plasma condition that drives spacecraft
surface charging.

## Domain quick reference

- Annex H tabulates order-of-magnitude plasma density and temperature
  reference values per space-environment region, for use when no
  mission-specific plasma model is available. Seven regions are
  covered here: ionosphere, plasmasphere, auroral, outer
  magnetosphere, solar wind, magnetosheath, and the magnetotail/L2
  environment.
- The regions split into two rough regimes: cold and dense (ionosphere,
  plasmasphere -- high density, sub-eV to low-eV temperature) and hot
  and tenuous (auroral, outer magnetosphere, magnetotail/L2 -- low
  density, hundreds to thousands of eV). Solar wind and magnetosheath
  sit between the two, with moderate density and moderate temperature.
- The hot, tenuous regions are the recognized drivers of spacecraft
  surface charging: a low ambient density limits the return current
  that would otherwise neutralize a charging surface, while the high
  temperature raises the incident current from energetic particles.
  This leaf flags that condition as a screening signal, not a
  computed charging voltage.
- Each region's reference range is an order-of-magnitude bound, not a
  precise design value; a candidate reading outside the range is a
  finding that the reference table does not cover the case, not
  necessarily an error in the reading.

## Workflow

1. Identify the mission orbit regime (e.g. a LEO pass through the
   ionosphere, a GEO mission in the outer magnetosphere, an
   interplanetary cruise in the solar wind, an L2 mission in the
   magnetotail/L2 environment) and select the applicable Annex H
   region for that regime. Reject a regime with no defined mapping
   before it enters the assessment.
2. Pull that region's reference density and temperature ranges.
3. Validate any candidate density or temperature reading (from a
   mission-specific model, a measurement, or an assumption) against
   the region's reference range: below, within, or above range.
4. When a single representative value is needed for a margin
   analysis (rather than a measured or modeled reading), derive it by
   log-space interpolation between the range's low and high bound at
   the desired fraction (0.0 = low bound, 1.0 = high bound, 0.5 = the
   geometric mean).
5. For a hot, tenuous region (auroral, outer magnetosphere,
   magnetotail/L2), screen the density/temperature pair for the
   surface-charging condition: flagged only when the region carries
   the charging-risk designation, the density reading is not above
   the reference range, and the temperature reading is not below it.
6. Record the selected region, the range-validation results, and the
   charging screen result as the plasma-environment basis for the
   downstream charging and materials analyses.

## Pitfalls

- Selecting a region by altitude alone and ignoring the mission
  regime -- the auroral region and the ionosphere can overlap in
  altitude but have very different reference density and temperature,
  and the wrong choice under- or over-states the environment.
- Treating an "above_range" or "below_range" classification as
  automatically wrong -- Annex H gives an order-of-magnitude bound for
  when no mission-specific model exists; an out-of-range reading means
  the table does not cover this case and a dedicated model is needed,
  not that the reading itself is invalid.
- Using the geometric-mean (fraction 0.5) representative value as a
  worst case -- for a margin analysis the worst case is typically the
  low-density/high-temperature end of a charging-risk region, which
  is the high end of the temperature range and the low end of the
  density range, not the midpoint of either.
- Flagging surface charging for any hot, tenuous region regardless of
  the actual reading -- a region's charging-risk designation is a
  property of the region, not a guarantee that a specific reading is
  in the hot/tenuous part of its range; the screen still checks the
  reading against the range.

## Behavior contract (gate 3)

The region-reference, range-validation, log-interpolation,
source-selection, and surface-charging-screen logic is exercised by
the gate 3 contract test: scripts/test_e1004_ref_plasma.py against
scripts/e1004_ref_plasma_logic.py (stdlib unittest, offline). Run:
python3 scripts/test_e1004_ref_plasma.py

## Compliance

- ECSS standards are freely downloadable (ESA); cite the source and
  paraphrase per standards-map.yaml.
- 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 →