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.
npx skills add TrueClicks/claude-plugins --skill skill-051-bid-simulator-analysis-target-changesgit clone --depth 1 https://github.com/TrueClicks/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/skills/trueclicks/claude-plugins/skill-051-bid-simulator-analysis-target-changes)<a href="https://agentmods.dev/skills/trueclicks/claude-plugins/skill-051-bid-simulator-analysis-target-changes"><img src="https://agentmods.dev/badge/skills/trueclicks/claude-plugins/skill-051-bid-simulator-analysis-target-changes.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 | $0.00032 | $0.00781 |
| Opus 5 | $0.00016 | $0.00391 |
| Sonnet 5 | $0.00006 | $0.00156 |
| Haiku 4.5 | $0.00003 | $0.00078 |
Grade A, and why
skill-051-bid-simulator-analysis-target-changes 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 8d 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill 051: Bid Simulator Analysis for Target Changes
Purpose
Bid simulators provide data-driven projections for target changes, showing trade-offs between volume and efficiency. This skill leverages simulator data to evaluate proposed target changes, quantify opportunity cost of current targets, and find optimal efficiency/volume balance.
Data Requirements
Data Source: Custom GAQL Required
Bid simulator data is not included in the standard export.
Standard Data:
data/account/campaigns/*/campaign.md- Current target settingsdata/performance/campaigns/*/campaign_metrics_30_days.md- Current performance
GAQL Queries:
Target CPA Simulator:
SELECT
campaign.id,
campaign.name,
campaign_simulation.type,
campaign_simulation.modification_method,
campaign_simulation.start_date,
campaign_simulation.end_date,
campaign_simulation.target_cpa_point_list.points
FROM campaign_simulation
WHERE campaign_simulation.type = 'TARGET_CPA'
AND campaign.status = 'ENABLED'
Target ROAS Simulator:
SELECT
campaign.id,
campaign.name,
campaign_simulation.type,
campaign_simulation.target_roas_point_list.points
FROM campaign_simulation
WHERE campaign_simulation.type = 'TARGET_ROAS'
AND campaign.status = 'ENABLED'
Run via /google-ads:get-custom with query names cpa_simulator and roas_simulator.
Analysis Steps
-
Retrieve simulator data: Query bid simulators for campaigns using Target CPA, Target ROAS, or budget simulators.
-
Parse simulation points: Extract target value, estimated impressions, clicks, conversions, cost, conversion value per point.
-
Analyze trade-off curves: Plot conversions vs target CPA, ROAS achieved vs target ROAS, marginal CPA for each increment.
-
Identify optimal points: Find targets that maximize conversions within efficiency constraints and align with business objectives.
-
Compare current vs optimal: Calculate additional conversions/revenue, cost change, efficiency change.
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.
- 8d ago First seen · 100 lines · 32 tokens per session scan A 34622ae6268a
skill-051-bid-simulator-analysis-target-changes is a skill published in the GitHub repository TrueClicks/claude-plugins (2 stars, last pushed 2mo ago), licensed MIT. It adds 32 tokens to every session and 781 once invoked, about $0.0002 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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