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/WYRE-AI/msp-claude-pluginsWrote 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/commands/wyre-ai/msp-claude-plugins/phishing-results)<a href="https://agentmods.dev/commands/wyre-ai/msp-claude-plugins/phishing-results"><img src="https://agentmods.dev/badge/commands/wyre-ai/msp-claude-plugins/phishing-results/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/commands/wyre-ai/msp-claude-plugins/phishing-results"><img src="https://agentmods.dev/badge/commands/wyre-ai/msp-claude-plugins/phishing-results.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 | $0.00013 | $0.00910 |
| Opus 5 | $0.00006 | $0.00455 |
| Sonnet 5 | $0.00003 | $0.00182 |
| Haiku 4.5 | $0.00001 | $0.00091 |
Grade A, and why
phishing-results 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 6d 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Phishing Results
Cross-vendor phishing-simulation results report: click-rate trend and named repeat clickers over the given window, pulled from whatever phishing-simulation platform the org has connected, with optional correlation against real-world click signal from a connected email-security tool where available.
Prerequisites
- Conduit gateway connected (
conduit) with at least one phishing-simulation connector. Without one, there is no simulation data to report.
Steps
-
Discover available tools. Call
conduit__search_toolsto determine which phishing-simulation connector is live and its actual tool names (e.g.knowbe4__list_campaigns). Also check for a connected email-security tool with phishing-adjacent signal (proofpoint__list_vap_users,avanan__list_threats) as optional enrichment — never assume it's present. -
Resolve the window. Parse
window(default90dif omitted). Accept shorthand like30d,90d,180d. Pull all campaigns whose run date falls within the window. -
Compute click-rate trend across the campaigns in the window, ordered chronologically, per the
phishing-simulation-analysisskill. Label trend direction as Improving / Flat / Worsening, or "insufficient history" if fewer than 3 campaigns fall within the window. -
Identify repeat clickers — users with 2+ failures within the window — sorted by failure count then recency. Cross-reference remedial-training completion for each.
-
Correlate with real-world signal where available. If an email-security tool with phishing-adjacent data is connected, check each repeat clicker for a matching real-world finding and flag any match as a compounding risk signal. If not connected, note explicitly that this enrichment wasn't performed.
Arguments
window(optional; default:90d) — Time window for the phishing-results report, e.g.30d,90d,180d.
Examples
Default 90-day window
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.
- 6d ago First seen · 115 lines · 13 tokens per session scan A 79795867ed08
phishing-results is a command published in the GitHub repository WYRE-AI/msp-claude-plugins (45 stars, last pushed 7d ago), licensed Apache-2.0. It adds 13 tokens to every session and 910 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 2026-09-04.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.