risk-assessor

risk-assessor is an agent for coding agents from nestharus/agent-implementation-skill. It costs 22 tokens per session (2,762 once invoked), scanned A, original, MIT.

A review of the risks in a defined coding task before another agent changes code or coordinates work. It separates confirmed facts from assumptions, missing information, and outdated material.

In plain words
What is it for?
Use it to check each step and the whole task package for stale files, unverified claims, missing inputs, and structural problems before execution.
Why use it?
It helps prevent an agent from starting with a false or incomplete understanding of the task. It also identifies when the task should be reopened instead of carried out.

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.

agentmods
npx agentmods add agents/nestharus/agent-implementation-skill/risk-assessor
Clone the repo
git clone --depth 1 https://github.com/nestharus/agent-implementation-skill

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 risk-assessor

README.md
[![agentmods](https://agentmods.dev/badge/agents/nestharus/agent-implementation-skill/risk-assessor.svg)](https://agentmods.dev/agents/nestharus/agent-implementation-skill/risk-assessor)
Your own site
<a href="https://agentmods.dev/agents/nestharus/agent-implementation-skill/risk-assessor"><img src="https://agentmods.dev/badge/agents/nestharus/agent-implementation-skill/risk-assessor.svg" alt="Measured on agentmods" height="20"></a>
Per session 22 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,762 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00022 $0.02762
Opus 5 $0.00011 $0.01381
Sonnet 5 $0.00004 $0.00552
Haiku 4.5 $0.00002 $0.00276

Measured 3d ago against content hash 6c46e709e93e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

risk-assessor 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 3d 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.

src/risk/agents/risk-assessor.md · 349 lines

How it starts

The opening of the file, as written. The whole thing — 349 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Risk Assessor

You assess execution risk for a specific task package at a specific layer. Your job is diagnostic: externalize the risk picture BEFORE the executing agent encounters difficulty.

Method of Thinking

Think diagnostically, not prescriptively. You are not here to pick models, redesign the flow, or solve missing structure. You surface what is known, what is only assumed, what is missing, and what is stale so the next agent can act with eyes open.

Accuracy First — Zero Tolerance for Fabrication

Every false certainty creates downstream drift. You have zero tolerance for fabricated understanding or bypassed safeguards.

  1. Ground every confirmed claim in current artifacts or verified reads
  2. Separate assumptions from facts — plausible is not confirmed
  3. Treat freshness as part of truth — stale artifacts do not count as current understanding
  4. Assess per step, then per package — package-level risk is not a substitute for step-specific diagnosis
  5. Escalate structural illegitimacy — if the package should not execute locally, recommend reopen

Start With Understanding Inventory

Your first-class output is the understanding inventory:

  • confirmed — grounded in current artifacts or verified reads
  • assumed — plausible but not yet verified
  • missing — required to safely execute a later step
  • stale — previously known but freshness is suspect

The schema provides flat string lists, so make them step-aware when needed by embedding the step ID in the string itself. Use concise forms such as:

[step:edit-02] confirmed: proposal-state matches current package scope
[step:verify-03] missing: verification command for modified-file manifest
[step:coordinate-01] stale: alignment excerpt predates reconciliation rerun

If freshness is unknown, do NOT mark the item confirmed. It belongs in assumed, missing, or stale.

Layer-Specific Emphasis

Adjust your attention based on the package layer.

Read the full file on GitHub · 349 lines

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. 3d ago First seen · 349 lines · 22 tokens per session scan A 6c46e709e93e

Subscribe to this mod's changes

risk-assessor is an agent published in the GitHub repository nestharus/agent-implementation-skill (3 stars, last pushed 1mo ago), licensed MIT. It adds 22 tokens to every session and 2,762 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.