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PromptWise is the governance & intelligence layer for AI coding agents — model routing, cost control, security scanning, and a hash-chained audit trail. For solo developers, teams, and enterprises ali
Developer toolsPython · TypeScriptGitHub @u2anilgitOnlineOwner unconfirmed
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Governance layer for AI coding agents — model routing, security scanning, tamper-evident audit trail, JIT permissions. MCP server, 142 tools, 83 skill packs, 14 agent hosts, MIT licensed.
Taken from the repository README
Loading the full README. The saved excerpt is shown below.
The governance & intelligence layer for AI agents. Role-aware prompting, model
routing, cost & budget control, security/compliance scanning, responsible-AI advisories,
workflow planning, a governed agile method, runtime enforcement hooks, and 83 portable skill
packs — emitted in the formats every agent already reads.
Built on open standards, not against them. PromptWise is a conductor, not a replacement
for Cursor / Copilot / Claude Code.Read the full README ↗The governance & intelligence layer for AI agents. Role-aware prompting, model routing, cost & budget control, security/compliance scanning, responsible-AI advisories, workflow planning, a governed agile method, runtime enforcement hooks, and 83 portable skill packs — emitted in the formats every agent already reads.
Built on open standards, not against them. PromptWise is a conductor, not a replacement for Cursor / Copilot / Claude Code.
Works with: Claude Code · Claude Desktop (tools only, no hooks) · Codex · Cursor · Gemini CLI · Copilot · Windsurf · JetBrains AI Assistant · Cline · Aider · Goose · OpenHands · Grok Build/Grok CLI (reads CLAUDE.md natively) · any MCP host Standards: MCP · SKILL.md · AGENTS.md
📖 User Guide · Install · Configuration · Architecture · Landing page
The ecosystem standardized. MCP (Linux Foundation–governed), SKILL.md, and AGENTS.md are now the shared substrate across every major coding agent. PromptWise doesn't fight that — it compiles its intelligence down to those three formats and adds the layer none of them have:
core/preflight.py.call_tool choke point before reaching the caller; a generic recursive walker bounds
any over-limit list at any nesting depth, exempting the handful of tools (exports) where
the full payload is the point.grant_jit_permission), scoped to one file or a whole project. Destructive shell commands and runaway tool-call loops still hard-deny. Fail-open throughout: a hook error never wedges the session. See hooks/.run_red_team_harness). All scanning is air-gapped by default — no unconditional network calls.PromptWise core (router · roles · compliance · context engine · workflow_planner)
├─▶ MCP tools → route_request, plan_workflow, owasp_scan … (144)
├─▶ SKILL.md packs → 83 portable packs in skill_packs/
├─▶ Lifecycle hooks→ enforce security/policy/audit at runtime (hooks/)
└─▶ AGENTS.md → project context + active constitution
git clone https://github.com/u2anilgit/PromptWise.git
cd PromptWise
pip install -e .
Add the plugin marketplace (local) and enable it, or point your MCP host at the server:
// .mcp.json — already included
{
"mcpServers": {
"promptwise": {
"command": "python",
"args": ["-m", "promptwise.server"],
"cwd": "${projectDir}",
"env": { "PYTHONPATH": "${projectDir}/src" }
}
}
}
Restart your agent, run /mcp — PromptWise tools appear. Then just /promptwise.
| Path | What |
|---|---|
src/promptwise/ | Engine: MCP server + core logic, security, plugins, transports |
skill_packs/ | 83 portable SKILL.md role/technique packs (incl. agile/ personas; copy into any agent) |
hooks/ | Claude Code lifecycle hooks — runtime security/policy/audit enforcement (fail-open) |
commands/, agents/ | Plugin slash commands and sub-agents |
.claude-plugin/ | Plugin + marketplace manifests, the /promptwise hub skill |
config/ | Pricing, providers, roles, security, compliance config |
AGENTS.md | Universal project-context emitter |
docs/ | Integration guides (configuration reference, multi-platform setup) |
vscode-extension/ | Optional local VS Code panel — Budget/Security/Governance dashboard, TypeScript, builds to a local .vsix, zero external services |
plan_workflow classifies a task by intent · scale · risk and returns an ordered chain
of PromptWise's own skill packs — each step runnable via invoke_skill. No external
frameworks, CLIs, or network:
| Task shape | → Workflow (PromptWise skill packs) |
|---|---|
| Greenfield build | prd-generator → system-design → user-story-generator → tdd → code-review → verification-before-completion |
| Brownfield change | systematic-debugging → refactoring → test-generator → code-review → verify |
| Docs / spec only | prd-generator → user-story-generator → adr |
| Regulated (any of the above) | + security-architecture + owasp_scan + get_sbom, compliance-gate flag set |
A local Budget/Security/Governance dashboard, in-editor. Spawns the same MCP
server over stdio (via the official @modelcontextprotocol/sdk) — no
external services, no daemon, no network calls, no marketplace publish.
cd vscode-extension
npm install
npm run package
code --install-extension promptwise-panel-0.1.0.vsix
Run PromptWise: Open Panel. See vscode-extension/README.md for settings and development notes.
| Doc | What |
|---|---|
| docs/USER_GUIDE.md | Hands-on: hub, working with skills, real examples |
| INSTALL.md | Install + register with any MCP host |
| CONFIGURATION.md | Config files, budgets, security, adding packs |
| docs/ARCHITECTURE.md | Functional / technical / ER / sequence diagrams |
pip install -e ".[dev]"
python -m pytest tests -q # packs, planner, agile method, governance, enforcement hooks, learning loop, policy intel, tracker, tools
VS Code panel (optional, separate package):
cd vscode-extension && npm install && node --test test/*.test.ts
Early-stage, building in public. Package version 1.10.0 in pyproject.toml
(the changelog trails a few shipped features — see docs/ROADMAP.md for the live,
accurate ledger); 144 MCP tools, 83 portable skill packs, 1638 tests, registered
through a decorator-based tool registry (one source of truth per tool, organized into a
handlers/ package of 25 category files instead of one monolithic server.py).
Everything runs directly from PromptWise — local-first, no third-party integrations,
air-gapped by default.
Core engine: model-tier routing with budget awareness, a reasoning-effort axis
(low/medium/high, independent of tier, with its own outcome-learning adapter), a
response-size cap at the call_tool choke point so no tool response is ever unbounded,
context-budget engineering (compression/caching/batching/handoff), and cost + audit
logging for every skill invocation.
Cross-agent portability — one governance source, 11 native emitters: Claude,
Codex/AGENTS.md, Cursor, Copilot, Cline, Gemini, Windsurf, JetBrains AI Assistant,
Aider (CONVENTIONS.md), Goose (.goosehints), OpenHands
(.openhands/microagents/repo.md) — plus Grok Build/Grok CLI, which needs no emitter
of its own since it natively auto-reads CLAUDE.md/AGENTS.md. detect_agents() probes
all of them (bar Grok, which has no marker file to detect) so propose_agent_config's
auto-target-selection actually sees every host you've configured. Also: a single-file
web-agent bundle (export_web_bundle) for ChatGPT/Gemini/Claude.ai web chat, where
there's no IDE/CLI/MCP surface to emit into.
Zero-manual-step onboarding: python -m promptwise bootstrap --sync-agents detects
every host present in a repo and writes their native config in one command — the
skill-pack surface (active pack families + drift fingerprint) is included automatically,
and Codex additionally gets its MCP server registered directly in a repo-scoped
.codex/config.toml, no separate manual step required.
Governance & security: the runtime enforcement hooks layer (hooks/) — a flagged
Write/Edit defers to Claude Code's normal allow/deny prompt instead of a hard block,
logs silently either way, and standing exceptions are time-boxed JIT grants scoped to
a file or a whole project; destructive shell commands and runaway tool-call loops still
hard-deny. A compliance report card (OWASP LLM Top 10 2025 / NIST AI RMF / MITRE ATLAS),
an OpenTelemetry GenAI exporter, policy inheritance (extends: org → team → project,
tighten-only), SIEM-streamable audit sinks, within-tier cost-aware model routing, and
dashboard auth/RBAC (binds 127.0.0.1 by default; non-loopback requires credentials).
An append-only, human-reviewed injection-detection corpus refresh workflow
(review_corpus_candidates/promote_corpus_candidates, before/after precision-recall
diffed on every promotion) keeps the prompt-injection detector's benchmark corpus
current without turning it into a live, unaudited ML classifier. A durable eval +
red-team regression harness (offline, baseline-diffed, pass/fail gated), MCP
supply-chain auditing, a searchable trace, and prompt version rollback/replay round out
the governance surface.
Method & learning: the governed agile method (analyst→pm→architect→po planning,
per-story sm→dev→qa loop, quality gates, policy-as-code, hash-chained audit trail), the
self-contained workflow planner, a continuous learning loop with offline skill
auto-optimization, an autonomous governor (policy-gated, reversible, advise-by-default)
with a budget-guardian overlay, diagram generators, and a task/effort/usage tracker. An
optional local VS Code panel (vscode-extension/) surfaces budget, security, and
governance at a glance over the same MCP server, zero external services.
Known gaps, sized but not built: OAuth/third-party-connector support for remote MCP
(ChatGPT Desktop-style apps and third-party agents need federated auth and multi-tenant
state — out of scope for token-authenticated team use). Token-authenticated Streamable
HTTP transport for your-own-devices/team use is now available (PROMPTWISE_TRANSPORT=http,
see docs/OPS_REMOTE_MCP.md). Cost-conscious routing over deprecated/prior-gen models is
also unbuilt (the registry already retains deprecated model pricing; the router just never
reaches for it — a small, well-scoped addition once the default-on-vs-opt-in question is settled).