sanad-agent: Skill for Codex

.agents/skills/sanad-reference-grounding/SKILL.md

sanad-reference-grounding is a skill for Codex from EastStarAI/sanad-agent. It costs 90 tokens per session (826 once invoked), scanned A, original, MIT.

A workflow for collecting and using evidence from external software projects when planning or implementing Sanad work. It stores detailed source notes separately from the project's tracked knowledge.

In plain words
What is it for?
Use it to create, update, read, or audit reference evidence for a task, especially when a plan or implementation depends on how another project works.
Why use it?
It gives developers a consistent way to verify decisions against outside references without filling the repository with source-specific research details.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: installed under .agents/ (shared by several agents); mentions AGENTS.md.

This is EastStarAI/sanad-agent's own configuration. It tells Codex how to work on sanad-agent itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything sanad-agent configures →

Reuse

Borrowing it

Nothing to install: this file belongs to EastStarAI/sanad-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/EastStarAI/sanad-agent/main/.agents/skills/sanad-reference-grounding/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/EastStarAI/sanad-agent

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 sanad-reference-grounding

README.md
[![agentmods](https://agentmods.dev/badge/skills/eaststarai/sanad-agent/sanad-reference-grounding/github.svg)](https://agentmods.dev/skills/eaststarai/sanad-agent/sanad-reference-grounding)
Your own site
<a href="https://agentmods.dev/skills/eaststarai/sanad-agent/sanad-reference-grounding"><img src="https://agentmods.dev/badge/skills/eaststarai/sanad-agent/sanad-reference-grounding/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 sanad-reference-grounding

Your own site · 80×15
<a href="https://agentmods.dev/skills/eaststarai/sanad-agent/sanad-reference-grounding"><img src="https://agentmods.dev/badge/skills/eaststarai/sanad-agent/sanad-reference-grounding.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 90 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 826 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 $0.00090 $0.00826
Opus 5 $0.00045 $0.00413
Sonnet 5 $0.00018 $0.00165
Haiku 4.5 $0.00009 $0.00083

Measured 12d ago against content hash 11feb410f5c8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

sanad-reference-grounding 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 12d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/resolve_packet.sh), 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.

.agents/skills/sanad-reference-grounding/SKILL.md · 74 lines

How it starts

The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Ground Sanad Work in External Evidence

Use one completion-oriented workflow for both evidence authoring and implementation. Publicly acknowledge that Sanad learns from external reference projects while keeping source-specific navigation details in the ignored local evidence store.

Choose the mode

  • Author or refresh: Use when planning a new reference-informed task, when no packet exists, or when a source revision changed.
  • Consume: Use when implementing or reviewing a task with a current packet.
  • Audit: Use after implementation to compare the result with adopted and adapted obligations.

Read references/evidence-packet-authoring.md completely before authoring, refreshing, discovering, or downloading sources.

Resolve before implementation

  1. Run scripts/resolve_packet.sh <task-id> from the primary checkout or a linked worktree.
  2. Follow the returned status:
    • ready: read the packet completely and continue in Consume mode.
    • authoring_required: enter Author mode and create the missing store data or packet.
    • refresh_required: enter Refresh mode and reconcile the changed source.
    • source_unavailable: exhaust catalog, public discovery, and authorized access options before blocking.
  3. Read the governing AGENTS.md and license for each selected source tree.
  4. Read any navigation_aid paths returned by the resolver when they accelerate discovery. Treat them as optional maps, not evidence authority.
  5. Inspect every mandatory source file, symbol, and test in the packet. Reports are navigation aids only; source and tests are authoritative.
  6. If a source working tree is dirty, determine whether the changed files overlap mandatory evidence. Do not treat unrelated dirt as a blocker and do not overwrite user changes.

Do not stop merely because a packet, catalog entry, or local clone is absent. Build or repair the recoverable evidence first, rerun the resolver, then continue implementation.

Read the full file on GitHub · 74 lines

Files

What ships with it

4 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. 12d ago First seen · 74 lines · 90 tokens per session scan A 11feb410f5c8

Subscribe to this mod's changes

sanad-reference-grounding is a skill published in the GitHub repository EastStarAI/sanad-agent (44 stars, last pushed 2d ago), licensed MIT. It adds 90 tokens to every session and 826 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 2026-08-30.