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/introduction-framingWrote 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/introduction-framing)<a href="https://agentmods.dev/skills/sillydaibo/reasflow-dev/introduction-framing"><img src="https://agentmods.dev/badge/skills/sillydaibo/reasflow-dev/introduction-framing.svg" alt="Measured on agentmods" 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 | $0.00022 | $0.01518 |
| Opus 5 | $0.00011 | $0.00759 |
| Sonnet 5 | $0.00004 | $0.00304 |
| Haiku 4.5 | $0.00002 | $0.00152 |
Grade A, and why
introduction-framing scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Installed Root
Resolve the installed reasflow-dev skills root before running packaged scripts:
REASFLOW_SKILLS_ROOT="${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 $HOME/.codex/reasflow-skills" >&2
exit 1
fi
fi
Introduction Framing
Required pipeline
Follow these steps in order. The scripts only prepare and validate deterministic artifacts; native Codex subagents perform evidence extraction and writing. Never call an LLM API from these scripts.
Set once:
SKILL_ROOT="$REASFLOW_PRIVATE_SKILLS_ROOT/intro/introduction-framing"
1. Prepare and delegate evidence tasks
Run one prepare command per source type found in the workspace:
# Survey / related works / gap
python3 "$SKILL_ROOT/scripts/extract-workspace-info.py" \
--mode prepare --source-type survey --workspace . --source survey/survey.md \
--output intro/tasks/survey.json --extracted-output intro/survey_info.json
# Method description
python3 "$SKILL_ROOT/scripts/extract-workspace-info.py" \
--mode prepare --source-type method --workspace . --source Alg_Exp/document/method.md \
--output intro/tasks/method.json --extracted-output intro/method_info.json
# Experiment results
python3 "$SKILL_ROOT/scripts/extract-workspace-info.py" \
--mode prepare --source-type experiment --workspace . --source Alg_Exp/experiment/results.md \
--output intro/tasks/experiment.json --extracted-output intro/experiment_info.json
# Theory / proofs
python3 "$SKILL_ROOT/scripts/extract-workspace-info.py" \
--mode prepare --source-type theory --workspace . --source prover/proof.md \
--output intro/tasks/theory.json --extracted-output intro/theory_info.json
What ships with it
3 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.
- 7d ago First seen · 164 lines · 22 tokens per session scan A f4091d25c0a5
introduction-framing is a skill published in the GitHub repository sillyDaibo/reasflow-dev (2 stars, last pushed 11d ago), licensed MIT. It adds 22 tokens to every session and 1,518 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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