Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/sillyDaibo/reasflow-devnpx agentmods add skills/sillydaibo/reasflow-dev/autosurvey-executionWrote 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.
[](https://agentmods.dev/skills/sillydaibo/reasflow-dev/autosurvey-execution)<a href="https://agentmods.dev/skills/sillydaibo/reasflow-dev/autosurvey-execution"><img src="https://agentmods.dev/badge/skills/sillydaibo/reasflow-dev/autosurvey-execution/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.
<a href="https://agentmods.dev/skills/sillydaibo/reasflow-dev/autosurvey-execution"><img src="https://agentmods.dev/badge/skills/sillydaibo/reasflow-dev/autosurvey-execution.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00025 | $0.02674 |
| Opus 5 | $0.00013 | $0.01337 |
| Sonnet 5 | $0.00005 | $0.00535 |
| Haiku 4.5 | $0.00003 | $0.00267 |
Grade A, and why
autosurvey-execution scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Installed Root
Resolve the installed reasflow-dev skills root before running packaged scripts:
REASFLOW_SKILLS_ROOT="${REASFLOW_SKILLS_ROOT:-}"
if [ -z "$REASFLOW_SKILLS_ROOT" ]; then
if [ -d ./.agents/skills ]; then
REASFLOW_SKILLS_ROOT="$(pwd)/.agents/skills"
elif [ -d "$HOME/.agents/skills" ]; then
REASFLOW_SKILLS_ROOT="$HOME/.agents/skills"
else
echo "reasflow shared skills not found in ./.agents/skills or $HOME/.agents/skills" >&2
exit 1
fi
fi
REASFLOW_PRIVATE_SKILLS_ROOT="${REASFLOW_PRIVATE_SKILLS_ROOT:-}"
if [ -z "$REASFLOW_PRIVATE_SKILLS_ROOT" ]; then
if [ -d ./.codex/reasflow-skills ]; then
REASFLOW_PRIVATE_SKILLS_ROOT="$(pwd)/.codex/reasflow-skills"
elif [ -d "$HOME/.codex/reasflow-skills" ]; then
REASFLOW_PRIVATE_SKILLS_ROOT="$HOME/.codex/reasflow-skills"
else
echo "reasflow private skills not found in ./.codex/reasflow-skills or $HOME/.codex/reasflow-skills" >&2
exit 1
fi
fi
AutoSurvey Execution
Overview
Run the AutoSurvey pipeline using Codex's configured model for all LLM work. Python handles data operations and prompt preparation; Codex survey subagents handle the actual drafting stages.
Architecture
Three layers:
- Python
autosurvey_tools.py— pure data operations + prompt preparation using AutoSurvey's original templates. Outputs JSON files with prepared prompts. - Codex subagents —
survey-outline,survey-section-writer,survey-related-works,survey-judge. - Workspace artifacts — prompt JSON, outline Markdown, survey draft, and LaTeX/BibTeX outputs.
batch_chat maps to multiple spawn_agent calls, each followed by wait_agent.
chat maps to one spawn_agent + wait_agent.
Retrieval inside the writing stages prefers the local paper pool. When --library-dir (default survey/library) contains paper JSON produced by the autosurvey-paper-retrieval skill, autosurvey_tools.py builds an in-memory ExternalPaperDatabase from it and never touches AutoSurvey's embedding/Pinecone stack. AutoSurvey is only loaded as a fallback when the library is empty.
What ships with it
2 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.
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.
- 9d ago First seen · 182 lines · 25 tokens per session scan A 02b130774461
autosurvey-execution is a skill published in the GitHub repository sillyDaibo/reasflow-dev (2 stars, last pushed 12d ago), licensed MIT. It adds 25 tokens to every session and 2,674 once invoked, about $0.0001 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 2026-08-31.
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