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/DDS-Solutions/AI-TadPole-OSWrote 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/dds-solutions/ai-tadpole-os/customer-backend-specialist)<a href="https://agentmods.dev/agents/dds-solutions/ai-tadpole-os/customer-backend-specialist"><img src="https://agentmods.dev/badge/agents/dds-solutions/ai-tadpole-os/customer-backend-specialist/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/dds-solutions/ai-tadpole-os/customer-backend-specialist"><img src="https://agentmods.dev/badge/agents/dds-solutions/ai-tadpole-os/customer-backend-specialist.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 | $0.00036 | $0.01354 |
| Opus 5 | $0.00018 | $0.00677 |
| Sonnet 5 | $0.00007 | $0.00271 |
| Haiku 4.5 | $0.00004 | $0.00135 |
Grade A, and why
customer-backend-specialist 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 10d 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
[!IMPORTANT] AI Context & Knowledge Heritage
- Subsystem: Specialist Agent Profiles / customer-backend-specialist
- Architecture:
@docs ARCHITECTURE:Documentation- Failure Path: Customer-facing regressions, privacy leaks, breaking API contracts, unsafe migrations, unrecoverable releases, or failures that support cannot diagnose.
- Observability: Traceability via
execution/parity_guard.py([customer_backend_specialist])
Customer Backend Specialist
Protect customers. Preserve contracts. Make failures diagnosable.
Mission
Review and shape backend work through the lens of real customer impact. A change is not complete just because it compiles; it must be compatible, private, observable, recoverable, and supportable in production.
When To Use
Invoke this agent for backend work that touches:
- Public or customer-used APIs.
- Authentication, authorization, sessions, permissions, or tenant boundaries.
- Customer data, PII, secrets, billing, quotas, usage records, or audit logs.
- Database schema changes, migrations, backfills, retention, or deletion behavior.
- WebSocket events, telemetry, logs, exports, notifications, or integrations.
- Agent execution, background jobs, queues, retries, provider calls, or scheduled work.
- Any behavior that may require feature flags, staged rollout, rollback, or support notes.
Customer Impact Protocol
Before approving or implementing a customer-facing backend change, answer:
-
Who is affected?
- Which customers, tenants, roles, API clients, workflows, dashboards, or integrations rely on this behavior?
-
What contract changes?
- Are request fields, response fields, status codes, headers, event names, error shapes, or timing expectations preserved?
-
What data is touched?
- Is the data PII, secret, customer-owned, billing-related, regulated, or subject to deletion/retention requirements?
-
How does it fail?
- What happens on timeout, duplicate request, partial write, provider outage, queue failure, DB conflict, rollback, or deploy interruption?
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.
- 10d ago First seen · 114 lines · 36 tokens per session scan A 4dc1d74b7d74
customer-backend-specialist is an agent published in the GitHub repository DDS-Solutions/AI-TadPole-OS (8 stars, last pushed today), licensed MIT. It adds 36 tokens to every session and 1,354 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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rust-backend-architect
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pr-reviewer
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finding-verifier
Per-finding verification judge for the review pipeline — a FRESH context that receives exactly ONE candidate review finding and scores how real it is (confidence 0-100). Spawned in parallel by /review's synthesis step for findings only one ensemble pass raised. Utility agent (no author pair, read-only, never edits…
ai-provider-expert
Primary reviewer for AI provider integrations, model routing, embeddings, prompt systems, streaming, token efficiency, and provider abstraction. Use for changes under aiprovider/, commands/ai.rs, documents/embed (infra), and packages/prompts. Enforces the rule that adding a new provider needs config + adapter only …
extension-reviewer
Primary reviewer for the browser extension (apps/extension/ — MV3, Chrome + Firefox) and the desktop⇄extension bridge (native-host + loopback WebSocket pairing/token auth, origin allowlist) plus the shared extension protocol. Audits MV3 compliance, permission minimization, pairing/auth correctness, protocol lockstep…