outline-agent

outline-agent is a skill for Codex from appleweiping/WEIPING_WIKI. It costs 99 tokens per session (1,364 once invoked), scanned A, original, MIT.

A planning tool for a research-paper pipeline that reads the research idea, experiment log, LaTeX template, and conference rules, then creates a structured JSON outline. JSON is a text format for representing structured data.

In plain words
What is it for?
Use it to produce plotting instructions, Introduction and Related Work search plans, and a section-by-section writing plan.
Why use it?
It turns scattered research materials into a shared plan for figures, literature searches, and paper sections.

Skill for Codex

Written for Codex: installed under .codex/.

Good fit Use it to produce plotting instructions, Introduction and Related Work search plans, and a section-by-section writing plan.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/appleweiping/weiping_wiki/outline-agent
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add appleweiping/WEIPING_WIKI --skill outline-agent
Clone the repo
git clone --depth 1 https://github.com/appleweiping/WEIPING_WIKI

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for outline-agent

README.md
[![agentmods](https://agentmods.dev/badge/skills/appleweiping/weiping_wiki/outline-agent/github.svg)](https://agentmods.dev/skills/appleweiping/weiping_wiki/outline-agent)
Your own site
<a href="https://agentmods.dev/skills/appleweiping/weiping_wiki/outline-agent"><img src="https://agentmods.dev/badge/skills/appleweiping/weiping_wiki/outline-agent/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for outline-agent

Your own site · 80×15
<a href="https://agentmods.dev/skills/appleweiping/weiping_wiki/outline-agent"><img src="https://agentmods.dev/badge/skills/appleweiping/weiping_wiki/outline-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 99 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,364 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00099 $0.01364
Opus 5 $0.00049 $0.00682
Sonnet 5 $0.00020 $0.00273
Haiku 4.5 $0.00010 $0.00136

Measured 5d ago against content hash 685512f9d7d6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

outline-agent scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/validate_outline.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

3 near-identical copies found in the catalogue:

.codex/skills/outline-agent/SKILL.md · 114 lines

How it starts

The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Outline Agent (Step 1)

Faithful implementation of the Outline Agent from PaperOrchestra (Song et al., 2026, arXiv:2604.05018, App. F.1, pp. 40–44).

Cost: 1 LLM call.

Your task

Read four input files from the workspace and produce a single JSON object at workspace/outline.json with three top-level keys:

  • plotting_plan — array of figure objects
  • intro_related_work_plan — object with introduction_strategy and related_work_strategy
  • section_plan — array of section objects, each with section_title and subsections[]

How to do it

  1. Read the verbatim prompt at references/prompt.md. This is the exact Outline Agent system prompt from the paper. Use it as your system message.
  2. Prepend the Anti-Leakage Prompt from ../paper-orchestra/references/anti-leakage-prompt.md.
  3. Read the four input files:
    • workspace/inputs/idea.md
    • workspace/inputs/experimental_log.md
    • workspace/inputs/template.tex
    • workspace/inputs/conference_guidelines.md
  4. Synthesize across all four — the global instruction in the prompt is "Do not analyze inputs in isolation. You must synthesize information across all provided documents for every step."
  5. Emit a single JSON object following the schema in references/outline-schema.md. Cross-check against references/outline_schema.json (machine-readable).
  6. Save to workspace/outline.json.
  7. Validate:
    python skills/outline-agent/scripts/validate_outline.py workspace/outline.json
    
    If validation fails, fix the JSON and re-validate. Do not proceed to Step 2 or Step 3 with an invalid outline — every downstream agent depends on this schema.

Hard rules from the prompt (do not violate)

These are excerpted from references/prompt.md. The validator enforces them.

Plotting plan (Directive 1)

  • plot_type MUST be exactly one of "plot" or "diagram".
  • data_source MUST be exactly one of "idea.md", "experimental_log.md", or "both".
  • aspect_ratio MUST be exactly one of: "1:1", "1:4", "2:3", "3:2", "3:4", "4:1", "4:3", "4:5", "5:4", "9:16", "16:9", "21:9".
  • figure_id MUST be a semantically meaningful snake_case identifier (e.g., fig_framework_overview, fig_ablation_study_parameter_sensitivity).
  • figure_id MUST NOT contain the word "Figure".

Read the full file on GitHub · 114 lines

Files

What ships with it

6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago First seen · 114 lines · 99 tokens per session scan A 685512f9d7d6

Subscribe to this mod's changes

outline-agent is a skill published in the GitHub repository appleweiping/WEIPING_WIKI (122 stars, last pushed 13d ago), licensed MIT. It adds 99 tokens to every session and 1,364 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Related

Other skills, from other repositories

instrument-data-to-allotrope

Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…

anthropics/knowledge-work-plugins · 123 tokens

exploratory-data-analysis

Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…

K-Dense-AI/scientific-agent-skills · 83 tokens

matlab

Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.

K-Dense-AI/scientific-agent-skills · 42 tokens

phylogenetics

Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.

K-Dense-AI/scientific-agent-skills · 68 tokens

research-engineer

An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.

davila7/claude-code-templates · 43 tokens

mapping-to-snomed

Maps clinical concept spans extracted by OpenMed to SNOMED CT concepts through a USER-SUPPLIED terminology server (the user's own Ontoserver, Snowstorm, or UMLS/UTS), never a bundled vocabulary. Use when the user wants to code findings, disorders, procedures, body structures, or substances to SNOMED CT, run an ECL…

maziyarpanahi/openmed · 205 tokens