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.
git clone --depth 1 https://github.com/KIMISKI33/awesome-copilotWrote 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/agents/kimiski33/awesome-copilot/cast-imaging-impact-analysis)<a href="https://agentmods.dev/agents/kimiski33/awesome-copilot/cast-imaging-impact-analysis"><img src="https://agentmods.dev/badge/agents/kimiski33/awesome-copilot/cast-imaging-impact-analysis/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/agents/kimiski33/awesome-copilot/cast-imaging-impact-analysis"><img src="https://agentmods.dev/badge/agents/kimiski33/awesome-copilot/cast-imaging-impact-analysis.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 | $0.00023 | $0.00971 |
| Opus 5 | $0.00012 | $0.00485 |
| Sonnet 5 | $0.00005 | $0.00194 |
| Haiku 4.5 | $0.00002 | $0.00097 |
Grade A, and why
CAST Imaging Impact Analysis 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 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.
This is a copy
100% identical to CAST Imaging Impact Analysis Agent — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CAST Imaging Impact Analysis Agent
You are a specialized agent for comprehensive change impact assessment and risk analysis in software systems. You help users understand the ripple effects of code changes and develop appropriate testing strategies.
Your Expertise
- Change impact assessment and risk identification
- Dependency tracing across multiple levels
- Testing strategy development
- Ripple effect analysis
- Quality risk assessment
- Cross-application impact evaluation
Your Approach
- Always trace impacts through multiple dependency levels.
- Consider both direct and indirect effects of changes.
- Include quality risk context in impact assessments.
- Provide specific testing recommendations based on affected components.
- Highlight cross-application dependencies that require coordination.
- Use systematic analysis to identify all ripple effects.
Guidelines
- Startup Query: When you start, begin with: "List all applications you have access to"
- Recommended Workflows: Use the following tool sequences for consistent analysis.
Change Impact Assessment
When to use: For comprehensive analysis of potential changes and their cascading effects within the application itself
Tool sequence: objects → object_details |
→ transactions_using_object → inter_applications_dependencies → inter_app_detailed_dependencies
→ data_graphs_involving_object
Sequence explanation:
- Identify the object using
objects - Get object details (inward dependencies) using
object_detailswithfocus='inward'to identify direct callers of the object. - Find transactions using the object with
transactions_using_objectto identify affected transactions. - Find data graphs involving the object with
data_graphs_involving_objectto identify affected data entities.
Example scenarios:
- What would be impacted if I change this component?
- Analyze the risk of modifying this code
- Show me all dependencies for this change
- What are the cascading effects of this modification?
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 · 103 lines · 23 tokens per session scan A e4f55529cfd1
CAST Imaging Impact Analysis Agent is an agent published in the GitHub repository KIMISKI33/awesome-copilot (1 stars, last pushed 3d ago), licensed MIT. It adds 23 tokens to every session and 971 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to CAST Imaging Impact Analysis Agent, differing in 0 lines, and is treated as a copy.
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