Luna through the Claude-shaped SDK path
real memo artifacts
specialist workflows completed
The first bake-off made Luna look unable to execute StrategyOS. An isolated rerun inside its native OpenAI Codex harness produced the opposite operational result: skills were selected, specialists ran, and real artifacts landed on disk.
This is not a model-ranking reversal. It is strong evidence that the earlier Luna failure was primarily a harness and wiring failure, not proof that Luna could not use StrategyOS.
Same StrategyOS source and Luna model family; materially different agent harness.
real memo artifacts
specialist workflows completed
real memo artifacts
multi-specialist workflows completed
Only observable execution counted. The agent's own claim that it used a skill or wrote a file was not accepted as evidence.
A practical attribution across prompt, model, and wiring.
| Candidate cause | Finding | Why |
|---|---|---|
| Bad system prompt | Not the main cause | The native run used the same StrategyOS source and reliably chose skills without adding keyword-trigger rules. Correct date injection still matters for artifact quality. |
| Unintelligent model | Capable, imperfect | Luna planned, delegated, synthesized, corrected specialist mistakes, and preserved uncertainty. It still missed the product-specific lane on both product-priority routing prompts. |
| Bad wiring | Primary suspect | The result changed when Luna received native Codex skill discovery, delegation, tool execution, and artifact handling. A restrictive local sandbox also reproduced a wiring failure before the isolated execution policy was corrected. |
The artifacts were inspected for business reasoning, not merely file existence.
Both memos used the injected date of 13 July 2026, respected the stated commercial cap, avoided double-counting, and refused to certify runway without cash and burn data.
Each run spawned two specialists and received both completions. The parent agent detected and corrected mistakes in specialist drafts instead of copying them blindly.
Two product-priority prompts chose generic universal strategy skills rather than a product-specific skill. Overall domain-lane accuracy was 6/8, not 8/8.
The two memos disclosed different timing conventions and produced different net SMB values. The reasoning was traceable, but the sample is too small to establish production reliability.
StrategyOS is mostly portable knowledge and workflow, but only if the host honors the contract around it.
Codex exposed StrategyOS skill metadata, selected a skill when relevant, and then opened the actual SKILL.md. This matches the native skills lifecycle rather than preloading the entire library.
Specialist work ran as distinct native branches with completion events. The score did not rely on role-play text that merely looked like delegation.
The test required files to exist in the temporary workspace. Native tool use converted consulting intent into inspectable output.
An initial read-only app-server canary selected skills but could not open them because nested sandbox setup blocked local execution. The isolated test worked only after using an appropriate sandbox for fixed benign prompts.
Prove the native path in Tegy's real operating constraints before revisiting the production model decision.
Use Luna through its native OpenAI harness with the same StrategyOS version, date injection, and tools Tegy intends to ship.
Make knowledge bases, helper scripts, and skill-relative paths available without relying on Claude-specific plugin directories.
Verify tool access, cancellation, reconnect, interrupted turns, artifact persistence, and questionnaire continuation under the Container runtime.
Target at least 30 strategic and 30 direct routing turns plus 10 deep artifact runs, including adversarial and ambiguous cases.
Improve discoverability based on observed misses without adding forbidden prompt-string triggers or hidden routing hacks.
The experiment was intentionally separate from production.
0.144.1 with native OpenAI gpt-5.6-luna at medium reasoning effort.1.0.1-beta at source commit d522316f64a659e9f3a980bf4429710b43f4bb28.SKILL.md path.Official platform documentation and Tegy's preceding decision reports.
Scope note: this is a small local diagnostic experiment, not a production benchmark. It establishes that a native integration is worth testing; it does not establish reliability, cost, latency, or quality parity at Tegy scale.