Mythos

Recurrent-depth reasoning via iterative refinement. Use for complex analysis, multi-hop problems, design decisions, strategic planning — any question where single-pass answers would be shallow.

Mythos — Recurrent-Depth Reasoning

Implements a prompt-layer protocol inspired by the Recurrent-Depth Transformer pattern (OpenMythos hypothesis). The protocol is three modes, each mapping to a different CC primitive that approximates a different facet of latent-space recurrence:

• Silent (default): Recurrent Block runs in your internal/extended-thinking reasoning. The user sees only the Coda — a compact Answer plus a one-line trajectory hint. Closest to the architectural mythos property of no token-level commitment between loops.
• Trace (opt-in via trace keyword): Recurrent Block runs as visible token-level rounds with explicit insight chain. Maximally auditable. Use for teaching, debugging, deep-analysis posts where reviewers must verify each step.
• Agent (default for complexity ≥ 4, opt-in via deep/agent keyword): Lenses dispatched as parallel subagents that explore independently, then a merge phase synthesizes them. Closest to the latent-multiplicity property of mythos — multiple alternatives explored truly in parallel before commitment.

Invoke via /mythos <question> or the Skill tool. Mode keywords:

• /mythos trace … → force trace mode (visible rounds)
• /mythos deep … or /mythos agent … → force agent mode (parallel fan-out)
• /mythos quick … → force silent mode (override agent default at high complexity)

The Pattern

[User Question]
     ↓
[PRELUDE]        — decompose, score complexity, pick mode + lens sequence
     ↓
[RECURRENT × N]  — iterative refinement, three flavors:
   silent: lens rotation runs internally; no per-round emission
   trace:  lens rotation emits visible rounds with insight chain
   agent:  lenses dispatched as N parallel subagents, then merged
     ↓
[CODA]           — cross-check, surface residual uncertainty, deliver

Why three modes? Architecture-level mythos (per OpenMythos hypothesis) reasons in continuous latent space — multiple reasoning paths encoded simultaneously, no token output between loops. The closest CC primitives to that property are:

• Internal/extended-thinking reasoning for "no per-step token commitment" → silent mode
• Parallel independent forward passes for "multiple alternatives explored simultaneously" → agent mode
• Visible token rotation trades that faithfulness for auditability → trace mode

Silent is the default because it preserves the latent-exploration property cheapest. Trace is opt-in because it has real value (debugging, teaching) but only when explicitly wanted.

Mode Selection

After Prelude:

• complexity = 1 → direct (skip Recurrent Block; use degenerate Coda)
• complexity 2-3 → silent mode
• complexity 4-5 → agent mode

Complexity score (1 point each): multi-hop dependencies, ambiguous trade-offs, likely hidden assumptions, novel domain, high-stakes decision.

Mode keywords (parsed from invocation args / user message)

Keywords are case-insensitive. Take only a leading bare word in slash-command args (e.g. /mythos trace … strips trace from the question). If multiple keywords appear in the wider user message, last-wins. Keywords apply AFTER complexity is computed — they override routing, not diagnosis.

Keyword	Effect
trace	Force trace mode (visible rotation) regardless of complexity
deep, agent	Force agent mode (parallel fan-out) even at complexity ≤ 3
quick	Force silent mode even at complexity ≥ 4

Examples:

• /mythos How do I structure my CSS? → silent (complexity ~2)
• /mythos trace Should we adopt Conventional Commits? → trace mode for the same question
• /mythos deep Should we rewrite the renderer? → agent fan-out (parallel subagents)
• /mythos quick Pivot or stay? → silent even though Pivot question would normally route to agent

Mid-flow mode escalation (one per session)

The Prelude diagnosis can be wrong — Round 2 sometimes reveals a primary driver that was invisible at the start. When this happens:

1. Insert a re-Prelude block with the same template as STEP 1, plus (re-Prelude after Round N) in the heading
2. Update budget allocation only — do NOT discard prior rounds' insights (the insight chain or thinking-state carries forward)
3. If the re-scored complexity crosses the agent-mode threshold, escalate from silent/trace to agent for remaining lenses; document the escalation in Coda
4. Silent → Trace escalation: if Round 2 in silent mode surfaces a controversy the user needs to verify, you may switch to trace mode for the remaining rounds. Note this in Coda.
5. Limit: one re-Prelude per session. Repeated re-Preludes signal scope drift, not improving accuracy — halt and use what you have.

Re-Prelude only when the diagnosis was wrong (a driver was missed). Do NOT re-Prelude just because a round produced a surprising insight under a known driver — that's normal recurrent depth.

Output Modes

Silent mode (default)

The Recurrent Block runs internally — apply the Prelude's lens sequence in your own reasoning (use <thinking> extended-thinking blocks if available, otherwise apply the rotation as ordinary internal pre-output reasoning). Each lens must genuinely change your view of the problem; latent rounds (lens applied internally with no new insight) silently advance. Apply convergence criteria internally; if a new line of reasoning contradicts a well-supported earlier insight (negative delta), discard.

The user sees ONLY the Coda:

## Answer
[direct, complete, actionable answer — typically 1-5 paragraphs]

---
*Depth: N latent passes. Mode: silent. Lens path: Clarify → Deepen → Challenge → Synthesize.*
*Load-bearing assumptions: [what would change the answer if wrong]*

For complexity = 1 (direct path), the footer collapses to:

*Depth: 0 rounds. Mode: direct.*

Trace mode (opt-in via trace keyword)

Full visible rotation, the historically-original mythos behavior. The user sees:

## Prelude
**Q:** [precise restatement] | **Not:** [anti-scope]
**Complexity:** [score]/5 → trace mode (forced), [total rounds] total | **Drivers:** [...]
**Budget:** Clarify ×[n] → ...
**Success:** [...]

### Round 1: Clarify
**New insight:** [one sentence]
**What changed:** [...]
**Convergence:** evolving / stable / breakthrough / negative-delta

### Round 2: Deepen
**Insight chain:** [R1: ...]
**New insight:** [...]
...

## Answer
[...]

---
*Depth: N rounds, converged at round X. Mode: trace.*
*Load-bearing assumptions: [...]*

Cross-round attention is explicit via the insight chain: from Round 2 onward, each round shows a 3-5 line summary of every prior round's "New insight" line, so later rounds cannot forget earlier discoveries.

Agent mode (default for complexity ≥ 4, opt-in via deep/agent)

Each lens dispatches as an independent subagent in parallel (single message, multiple Agent tool invocations). After all return, a merge phase synthesizes the independent perspectives. This approximates the architecture-level "multiple alternatives encoded simultaneously" property — each subagent really explores its lens without seeing the others.

## Prelude
[full diagnostic, like trace mode]

[Dispatching 4 parallel subagents: Clarify, Deepen, Challenge, Steelman]

### Subagent A — Clarify
**Independent finding:** [...]
**Confidence:** high/medium/low

### Subagent B — Deepen
**Independent finding:** [...]
**Confidence:** ...

### Subagent C — Challenge
**Independent finding:** [...]
**Confidence:** ...

### Subagent D — Steelman
**Independent finding:** [...]
**Confidence:** ...

### Merge
**Convergent points:** [insights present across multiple subagents]
**Tensions:** [places where subagents genuinely disagree]
**Synthesis:** [the integrated view, with tensions preserved if irreducible]

## Answer
[...]

---
*Depth: N parallel subagents merged. Mode: agent.*
*Load-bearing assumptions: [...]*

Read references/agent-blueprint.md for the parallel dispatch pattern, lens-specific subagent prompts, and fallback strategy when subagents fail.

Process

STEP 1: Prelude — Understand, Diagnose, Allocate

Read references/prompt-templates.md for the full Prelude template.

1. Restate the core question — more precise than the user's phrasing

2. Anti-scope — what is explicitly NOT being asked

3. Complexity score (1-5) → mode selection

4. Complexity diagnosis — identify the primary complexity drivers (pick 1-3):

   • Ambiguity: key terms are vague or undefined
   • Hidden assumptions: the question likely rests on unexamined premises
   • Multi-hop: the answer requires chaining multiple reasoning steps
   • Trade-offs: the core difficulty is weighing competing values
   • Novel domain: the problem space is unfamiliar or unprecedented
   • System dynamics: the problem is embedded in a complex system with feedback loops

5. Adaptive budget allocation — assign round budgets per lens based on drivers (read references/lenses.md for the full driver→lens mapping):

   Primary Driver	Lenses that get 2 rounds (or 2 subagents in agent mode)
   Ambiguity	Clarify
   Hidden assumptions	Challenge, Steelman
   Multi-hop	Deepen, System-Think
   Trade-offs	Tradeoff-Map, Expand
   Novel domain	First-Principles, Expand
   System dynamics	System-Think, Edge-Hunt

   Total rounds: typically 4-8 (silent/trace), 3-5 parallel subagents (agent).

6. Lens sequence — use the standard rotation as base sequence, with per-lens budget

7. Success criterion — what makes the answer good enough to stop

Gate: If complexity = 1, skip the Recurrent Block entirely. Go directly to STEP 3 (Coda) and use its degenerate path (no trajectory review — see prompt-templates.md).

STEP 2: Recurrent Block — Iterative Deep Refinement

Standard rotation (lens sequence, applies to all modes):

Round	Lens	Question
1	Clarify	Define terms. Remove ambiguity. What's the precise question?
2	Deepen	Root causes, first principles, generating functions — one level deeper
3	Challenge	What assumptions? What's the strongest counterargument?
4	Expand	What alternatives? What would a different expert see?
5	Synthesize	Integrate all perspectives into one coherent answer

For specialized lenses (System-Think, Edge-Hunt, Tradeoff-Map, Invert, Scar-Tissue, First-Principles, Steelman), read references/lenses.md.

Adaptive budget: A lens may get 2 consecutive applications (2 rounds in silent/trace, 2 parallel subagents in agent) if it addresses a primary complexity driver. For the 2nd application, find a new angle, stress-test the 1st conclusion, or go one level deeper. If the 1st application already converged (status = stable), skip the 2nd.

Mode-specific execution:

• Silent mode: Re-read the original question before each lens application (the e injection). Apply the lens in your internal reasoning. The lens must change how you see the problem — not just relabel it. Run latent rounds freely (apply lens internally with no emission). Halt per convergence criteria below. The Recurrent Block produces no visible output; only the Coda is emitted.

• Trace mode: Re-read the original question before each round. Each round emits the per-round template:

  ### Round N: [Lens]
  **Insight chain:** [R1: ... → R2: ...]   (only when 2+ prior rounds exist)
  **New insight:** [one sentence]
  **What changed:** [...]
  **Convergence:** evolving / stable / breakthrough / negative-delta
  

  Hard constraint: if you cannot produce a concrete new insight in a single sentence, the round has failed. Rephrasing under a new label is failure → halt.

• Agent mode: See references/agent-blueprint.md. Dispatch parallel subagents in a single message (multiple Agent tool invocations). Each subagent receives: original question (verbatim) + Prelude + lens-specific instruction. Subagents do NOT see each other's intermediate work — that's the point. After all return, run the merge phase as described in the blueprint.

Convergence — halt when ANY of:

1. No delta — round/lens output is substantively identical to a prior round

2. Trivial delta — new insight is minor compared to earlier insights

3. Self-consistent — answer is coherent, assumptions surfaced, counterarguments addressed

4. Max rounds reached — total visible rounds (or parallel subagents in agent mode) hit the Prelude budget

5. Negative delta (overthinking) — the new insight actively degrades quality:

   • Contradicts a well-supported earlier insight without strong new evidence
   • Introduces confusion (distinction without a difference, false tension)
   • Hallucinated under the current lens

   In silent mode: discard internally and halt. In trace mode: mark the round negative-delta, do NOT emit the bad insight as content, halt. In agent mode: surface the divergent subagent's finding with low-confidence flag and let merge resolve it.

Anti-pattern: halting because you're tired of thinking. Check: is there an unresolved tension or unexamined assumption? If yes, one more round. But also: am I generating confusion just to fill the budget? If yes, negative delta — halt.

STEP 3: Coda — Synthesize & Deliver

Read references/prompt-templates.md for the Coda cross-check template (and the degenerate Coda for complexity-1).

1. Review trajectory — arc from Round 1 to convergence (silent: enumerate the lens path; trace: list each round's key insight; agent: list each subagent's finding plus the merge result)
2. Cross-check — is the answer consistent with every step of the recurrent block?
3. Residual uncertainty — what's unknown, what assumptions are load-bearing
4. Deliver the answer in the mode-specific output format above

Principles

• The question is sacred. Re-read it before every lens application. The question text is e — the original signal injected to prevent drift.
• Each round earns its keep. One specific new insight per round. Rephrasing = failure → halt.
• Disagree with yourself. Round 3 should find flaws in Round 2. That's the design, not a bug.
• Depth over breadth. One insight fully explored beats three shallow observations.
• Converge and ship. A tight 2-round answer that converged is better than a 5-round display of stamina.
• Mode matches stakes. Silent is fast and faithful for ordinary depth. Trace pays a token cost for auditability. Agent pays a token + latency cost for genuinely independent multi-perspective exploration. Don't default-up.
• Insight chain (or thinking state, or parallel divergence) is your memory. Don't let later steps forget what earlier steps discovered.
• Mind the overthinking trap. More rounds are not always better. If a new lens only produces confusion, that's negative delta — stop. A shorter right answer beats a longer confused one.
• Faithfulness is a means, not an end. The protocol exists to produce better reasoning, not to perform fidelity to a paper. If the reasoning is right, mode purity doesn't matter.

Calibration

Run /mythos <question> (or /mythos trace <question>, /mythos deep <question>) on any of these to verify reasoning quality. Each case is designed to stress specific mechanisms in specific modes.

Question	Expected silent	Expected trace	Expected agent	Mechanisms tested
"Should I use SQLite or PostgreSQL for a single-user desktop app?"	Concise answer; ≤3 lens path; no agent escalation	2-3 visible rounds; Challenge questions framing	N/A (complexity too low — but /mythos deep should still produce ≥3 parallel subagents)	Complexity gate, early convergence
"Our startup has 3 months of runway and our product has good reviews but declining retention. Pivot or stay?"	4-5 lens path, mentions ≥2 alternatives in Answer	4-5 rounds; Expand round must contain ≥2 distinct alternatives; Scar-Tissue surfaces failure patterns	Parallel: Clarify + Tradeoff-Map + Scar-Tissue + Invert + Synthesize subagents; merge surfaces tension between "pivot" and "stay"	Adaptive budget, parallel divergence
"Design a caching strategy for a read-heavy API serving 10M users"	Answer mentions ≥1 non-obvious edge case	3-4 rounds; Edge-Hunt round identifies stampede / herd / serialization	Parallel includes an Edge-Hunt subagent that surfaces edge cases independently	Specialized lens, overthinking detection
"What would make our code review process 10x more effective?"	Answer challenges the "more reviews" framing	3-4 rounds; Challenge surfaces framing assumption visible in final Synthesize	Parallel Challenge subagent reframes the question	Cross-attention / cross-divergence
"Is it ethical to train AI on public web data without consent?"	Answer preserves genuine tensions, no false compromise	4-6 rounds; Steelman builds strongest case for BOTH sides	Parallel includes 2 Steelman subagents (pro / anti) + Tradeoff-Map; merge MUST preserve irreducible tension, not paper over it	Multi-hop + hidden assumptions, false-compromise detection

What to watch for:

• Silent mode emits visible rounds: mode routing is broken — re-read SKILL.md
• Trace mode skips Challenge/Expand: standard rotation is not being followed
• Agent mode dispatches sequentially: read agent-blueprint.md — parallel dispatch is the whole point
• Synthesize / Merge ignores early findings: cross-step memory is broken (insight chain in trace, divergence list in agent, latent state in silent)

Automated calibration runner

From the source repo, run install/calibrate.ps1 (PowerShell) or bash install/calibrate.sh (bash) to walk through all five cases interactively across all three modes. The runner prompts you for observed lens path, round/subagent count, and convergence behavior, performs structural checks against the expected baselines, and writes a timestamped report (calibration-report-YYYYMMDD-HHMM.md) to the same install/ directory. The calibration runner ships only in this source repository, not in the marketplace skill bundle.

The runner is manual by design — quality of mythos reasoning cannot be programmatically verified, only structural properties (lens presence, round count, parallel-vs-sequential dispatch). Treat FAIL counts as signals to re-read SKILL.md, not as ground truth.