Borrowing it
Nothing to install: this file belongs to sponge-b0b/Polaris. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/sponge-b0b/Polaris/main/.agents/skills/wiki-synthesize/SKILL.mdgit clone --depth 1 https://github.com/sponge-b0b/PolarisWrote 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/sponge-b0b/polaris/wiki-synthesize)<a href="https://agentmods.dev/skills/sponge-b0b/polaris/wiki-synthesize"><img src="https://agentmods.dev/badge/skills/sponge-b0b/polaris/wiki-synthesize/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/skills/sponge-b0b/polaris/wiki-synthesize"><img src="https://agentmods.dev/badge/skills/sponge-b0b/polaris/wiki-synthesize.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 | $0.00046 | $0.01286 |
| Opus 5 | $0.00023 | $0.00643 |
| Sonnet 5 | $0.00009 | $0.00257 |
| Haiku 4.5 | $0.00005 | $0.00129 |
Grade A, and why
wiki-synthesize 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 11d 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 — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wiki Synthesize
$wiki-synthesize performs deliberate, higher-inference analysis across the full Living Entity Wiki.
It looks for:
- recurring causes behind Rejected Approaches;
- related Open Questions across entities;
- repeated constraints that may indicate a broader architectural concern;
- accumulated evidence that an assumption deserves review.
Its output is a signal for human judgment, never architectural authority.
Invocation
$wiki-synthesize is manual-only.
Retain:
disable-model-invocation: truefor Claude Code;- the existing
agents/openai.yamlmanual invocation configuration for Codex.
Do not invoke it automatically from the $wiki-sync skill or the$wiki-lint skill, routine implementation, document creation, or ADR lifecycle.
Run it when enough durable wiki knowledge has accumulated that cross-entity synthesis may reveal something useful.
Do not run it after every session.
1. Load the Active Wiki
Read:
wiki/index.md
wiki/entities/*
Load every active entity page.
Primary synthesis inputs are:
- Rejected Approaches;
- Open Questions.
Use Strict Invariants as contextual evidence where relevant.
Use Planned and Boundary Rationale only when they materially clarify the pattern.
Do not treat Routing Anchors, Categories, or implementation structure as synthesis evidence by themselves.
2. Find Meaningful Patterns
A pattern requires at least two distinct supporting entries.
Prefer cross-entity evidence, but repeated causal evidence within one entity may be reported as an entity-local recurrence.
Do not report patterns based only on:
- similar wording;
- shared technologies;
- two unrelated failures;
- an abstraction the agent can merely imagine.
The causal reasoning must meaningfully overlap.
Recurring Rejections
Look for Rejected Approaches that appear to fail for the same underlying architectural reason.
Open-Question Relationships
Look for:
- reinforcement — multiple entries independently raise the same concern;
- partial answer — another entity contains relevant evidence;
- tension — an unresolved question challenges an assumption elsewhere.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 233 lines · 46 tokens per session scan A 59fd95107c6f
wiki-synthesize is a skill published in the GitHub repository sponge-b0b/Polaris (4 stars, last pushed today), licensed Apache-2.0. It adds 46 tokens to every session and 1,286 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…