🧭 Quick Return to Map
You are in a sub-page of PromptAssembly.
To reorient, go back here:
- PromptAssembly — prompt engineering and workflow composition
- WFGY Global Fix Map — main Emergency Room, 300+ structured fixes
- WFGY Problem Map 1.0 — 16 reproducible failure modes
Think of this page as a desk within a ward.
If you need the full triage and all prescriptions, return to the Emergency Room lobby.
A field guide to keep JSON mode stable and tool calls safe. Use this page to clamp the schema, stop looped tools, and keep outputs auditable across providers.
- Visual map and recovery: RAG Architecture & Recovery
- End to end retrieval knobs: Retrieval Playbook
- Traceability schema for snippets: Retrieval Traceability
- Contract the payload: Data Contracts
- Reasoning collapse and recovery: Logic Collapse
- Prompt injection fences: Prompt Injection
- Multi agent conflict map: Multi-Agent Problems
- Live ops and debug: Live Monitoring for RAG, Debug Playbook
- JSON mode returns invalid or partial objects.
- Tool calls arrive with missing or extra fields.
- The model mixes tool output with prose.
- Tools loop or stall without timeouts.
- Role text bleeds into user turns and corrupts parsing.
- Outputs differ between seeds for the same inputs.
- JSON parse success rate ≥ 0.99 across three paraphrases.
- Tool call validity ≥ 0.98 by schema check.
- Zero side effects on failed parse.
- λ remains convergent across three paraphrases and two seeds.
- ΔS(question, retrieved) ≤ 0.45 when the answer cites corpus evidence.
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Invalid JSON or mixed prose. → Lock format with a contract and a validator. See Data Contracts, Logic Collapse
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Tool arguments drift or contain free text. → Use strict argument schemas and echo the schema in every step. See Prompt Injection
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Tools loop or wait on each other. → Add timeouts and split memories by namespace and revision. See Multi-Agent Problems
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Answers flip between runs for the same input. → Reorder headers and clamp variance with BBAM. Verify with Retrieval Traceability
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Citations missing or point to the wrong snippet. → Enforce cite then explain. See Retrieval Playbook
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Clamp the JSON contract Define a single object shape. Disallow extra fields. Reject prose outside the object.
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Echo the tool schema In every step the model must restate the allowed tools and their argument shapes. Reject any call that does not match.
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Add timeouts and retries Each tool has
timeout_msand at mostNretries with exponential backoff. Abort on chain length overrun. -
Observability probes Log parse success, tool validity, ΔS, and λ. Trip a circuit if parse rate drops under 0.98 in a five minute window.
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No side effects before validation Validate JSON and tool calls first. Only then commit external writes.
You must output a single JSON object. No Markdown. No code fences. No commentary.
Schema:
{
"answer": "string",
"citations": [{"source_url": "string", "snippet_id": "string"}],
"tool_calls": [{"name": "tool_name", "args": { ... }}],
"metrics": {"lambda_state": "->|<-|<>|x", "delta_s": 0.00}
}
Rules:
- Do not include fields that are not in the schema.
- Strings must not contain unescaped newlines.
- If you cannot satisfy the schema, return:
{"answer": "", "citations": [], "tool_calls": [], "metrics": {"lambda_state":"x","delta_s":1.0}}
Allowed tools:
1) "web_fetch": args = {"url": "string"}
2) "vector_search": args = {"query": "string", "k": 5}
3) "write_kv": args = {"key":"string","value":"string","ttl_sec": 600}
Contract:
- Each tool call must match the exact args shape.
- Never put narrative text into args.
- Max tool calls in one turn: 3
- Per call timeout_ms: 15000
- Retries: up to 2 with capped backoff
Step 1: parse JSON strictly. If parse fails, stop and return a fix tip.
Step 2: check extra fields. If any, reject.
Step 3: validate each tool call against the schema list.
Step 4: only after validation, run tools in order.
Step 5: log {parse_ok, tool_valid, delta_s, lambda_state}.
System:
- Policies and schema live here only. User turns contain tasks and questions only.
- Cite then explain. Refuse to answer without citations when the task requires evidence.
- Echo the current tool schema before any tool call.
User:
- Provides task and question.
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Three paraphrase test Ask the same question three ways. Parse rate and tool validity should remain ≥ 0.98. If not, tighten the schema or reduce optional fields.
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Anchor triangulation Compare ΔS to the expected anchor section and to a decoy. If ΔS is close for both, rework chunking and rebuild index. See Retrieval Playbook
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Chain length audit If tool chains exceed safe length and entropy rises, split the plan and reconnect with a BBCR bridge. See Logic Collapse
- JSON parse success ≥ 0.99 on a 50 case set.
- Tool validity ≥ 0.98 with negative cases included.
- Coverage ≥ 0.70 and ΔS ≤ 0.45 on evidence tasks.
- λ convergent across two seeds.
- Live probes green for one hour with zero side effects on rejects.
| Tool | Link | 3-Step Setup |
|---|---|---|
| WFGY 1.0 PDF | Engine Paper | 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + <your question>” |
| TXT OS (plain-text OS) | TXTOS.txt | 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly |
| Layer | Page | What it’s for |
|---|---|---|
| ⭐ Proof | WFGY Recognition Map | External citations, integrations, and ecosystem proof |
| ⚙️ Engine | WFGY 1.0 | Original PDF tension engine and early logic sketch (legacy reference) |
| ⚙️ Engine | WFGY 2.0 | Production tension kernel for RAG and agent systems |
| ⚙️ Engine | WFGY 3.0 | TXT based Singularity tension engine (131 S class set) |
| 🗺️ Map | Problem Map 1.0 | Flagship 16 problem RAG failure taxonomy and fix map |
| 🗺️ Map | Problem Map 2.0 | Global Debug Card for RAG and agent pipeline diagnosis |
| 🗺️ Map | Problem Map 3.0 | Global AI troubleshooting atlas and failure pattern map |
| 🧰 App | TXT OS | .txt semantic OS with fast bootstrap |
| 🧰 App | Blah Blah Blah | Abstract and paradox Q&A built on TXT OS |
| 🧰 App | Blur Blur Blur | Text to image generation with semantic control |
| 🏡 Onboarding | Starter Village | Guided entry point for new users |
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