Agent skill

Architectural Proposals

by FritzAndFriends in FritzAndFriends/SharpSite

How to write comprehensive architectural proposals that drive alignment before code is written

MITAuto-check passedSales & Support

Install Architectural Proposals

skills CLI
$ npx skills add FritzAndFriends/SharpSite --skill architectural-proposals -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install FritzAndFriends/SharpSite architectural-proposals --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/FritzAndFriends/SharpSite.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.copilot/skills/architectural-proposals .claude/skills/architectural-proposals && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
architectural-proposals
GitHub stars
145
Used in
2 other repos
Token cost
~1.6k tokens
SKILL.md length
567 words
Files
1
Skills in repo
18
Repo updated
First seen
Licence
MIT

At a glance

How to write comprehensive architectural proposals that drive alignment before code is written

  • Works in 7 steps: Problem Statement — Why current state is… → Proposed Architecture — Solution with… → What Changes — Impact on existing work… → …
  • Tasks that involve Proposals and quotes
  • SKILL.md covers Context, Patterns, Examples and Anti-Patterns
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Architectural Proposals is an agent skill from FritzAndFriends/SharpSite. How to write comprehensive architectural proposals that drive alignment before code is written

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Sales & Support, covering Proposals and quotes. The repository describes itself as: A basic CMS built with .NET 9 and Blazor. The licence is MIT.

When your agent uses it

  • Tasks that involve Proposals and quotes

Example prompts

  • “/architectural-proposals”

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Problem Statement — Why current state is broken (specific, measurable evidence)
  2. Proposed Architecture — Solution with technical specifics (not hand-waving)
  3. What Changes — Impact on existing work (waves, milestones, modules)
  4. What Stays the Same — Preserve existing functionality (no regression)
  5. Key Decisions Needed — Explicit choices with recommendations
  6. Risks and Mitigations — Likelihood + impact + mitigation strategy
  7. Scope — What's in v1, what's deferred (timeline clarity)

What it can do on your machine

Read from SKILL.md and the folder at commit c35e5e0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Architectural Proposals loads about 1.6k tokens when it runs. Until then it costs about 30 tokens; SKILL.md has 567 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~30
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from FritzAndFriends/SharpSite at commit c35e5e0, republished under its MIT licence (© FritzAndFriends). 567 words, ~1,569 tokens.

Download SKILL.mdSave it as .claude/skills/architectural-proposals/SKILL.md (or your agent's skills folder).
name
architectural-proposals
description
How to write comprehensive architectural proposals that drive alignment before code is written
domain
architecture, product-direction
confidence
high
source
earned (2026-02-21 interactive shell proposal)

Context

Proposals create alignment before code is written. Cheaper to change a doc than refactor code. Use this pattern when:

  • Architecture shifts invalidate existing assumptions
  • Product direction changes require new foundation
  • Multiple waves/milestones will be affected by a decision
  • External dependencies (Copilot CLI, SDK APIs) change

Patterns

Proposal Structure (docs/proposals/)

Required sections:

  1. Problem Statement — Why current state is broken (specific, measurable evidence)
  2. Proposed Architecture — Solution with technical specifics (not hand-waving)
  3. What Changes — Impact on existing work (waves, milestones, modules)
  4. What Stays the Same — Preserve existing functionality (no regression)
  5. Key Decisions Needed — Explicit choices with recommendations
  6. Risks and Mitigations — Likelihood + impact + mitigation strategy
  7. Scope — What's in v1, what's deferred (timeline clarity)

Optional sections:

  • Implementation Plan (high-level milestones)
  • Success Criteria (measurable outcomes)
  • Open Questions (unresolved items)
  • Appendix (prior art, alternatives considered)
Tone Ceiling Enforcement

Always:

  • Cite specific evidence (user reports, performance data, failure modes)
  • Justify recommendations with technical rationale
  • Acknowledge trade-offs (no perfect solutions)
  • Be specific about APIs, libraries, file paths

Never:

  • Hype ("revolutionary", "game-changing")
  • Hand-waving ("we'll figure it out later")
  • Unsubstantiated claims ("users will love this")
  • Vague timelines ("soon", "eventually")
Wave Restructuring Pattern

When a proposal invalidates existing wave structure:

  1. Acknowledge the shift: "This becomes Wave 0 (Foundation)"
  2. Cascade impacts: Adjust downstream waves (Wave 1, Wave 2, Wave 3)
  3. Preserve non-blocking work: Identify what can proceed in parallel
  4. Update dependencies: Document new blocking relationships

Example (Interactive Shell):

  • Wave 0 (NEW): Interactive Shell — blocks all other waves
  • Wave 1 (ADJUSTED): npm Distribution — shell bundled in cli.js
  • Wave 2 (DEFERRED): SquadUI — waits for shell foundation
  • Wave 3 (ADJUSTED): Public Docs — now documents shell as primary interface
Decision Framing

Format: "Recommendation: X (recommended) or alternatives?"

Components:

  • Recommendation (pick one, justify)
  • Alternatives (what else was considered)
  • Decision rationale (why recommended option wins)
  • Needs sign-off from (which agents/roles must approve)

Example:

### 1. Terminal UI Library: `ink` (recommended) or alternatives?

**Recommendation:** `ink`  
**Alternatives:** `blessed`, raw readline  
**Decision rationale:** Component model enables testable UI. Battle-tested ecosystem.

**Needs sign-off from:** Brady (product direction), Fortier (runtime performance)
Risk Documentation

Format per risk:

  • Risk: Specific failure mode
  • Likelihood: Low / Medium / High (not percentages)
  • Impact: Low / Medium / High
  • Mitigation: Concrete actions (measurable)

Example:

### Risk 2: SDK Streaming Reliability

**Risk:** SDK streaming events might drop messages or arrive out of order.  
**Likelihood:** Low (SDK is production-grade).  
**Impact:** High — broken streaming makes shell unusable.

**Mitigation:**
- Add integration test: Send 1000-message stream, verify all deltas arrive in order
- Implement fallback: If streaming fails, fall back to polling session state
- Log all SDK events to `.squad/orchestration-log/sdk-events.jsonl` for debugging
Show full SKILL.md (237 more words)Show less

Examples

File references from interactive shell proposal:

  • Full proposal: docs/proposals/squad-interactive-shell.md
  • User directive: .squad/decisions/inbox/copilot-directive-2026-02-21T202535Z.md
  • Team decisions: .squad/decisions.md
  • Current architecture: docs/architecture/module-map.md, docs/prd-23-release-readiness.md

Key patterns demonstrated:

  1. Read user directive first (understand the "why")
  2. Survey current architecture (module map, existing waves)
  3. Research SDK APIs (exploration task to validate feasibility)
  4. Document problem with specific evidence (unreliable handoffs, zero visibility, UX mismatch)
  5. Propose solution with technical specifics (ink components, SDK session management, spawn.ts module)
  6. Restructure waves when foundation shifts (Wave 0 becomes blocker)
  7. Preserve backward compatibility (squad.agent.md still works, VS Code mode unchanged)
  8. Frame decisions explicitly (5 key decisions with recommendations)
  9. Document risks with mitigations (5 risks, each with concrete actions)
  10. Define scope (what's in v1 vs. deferred)

Anti-Patterns

Avoid:

  • ❌ Proposals without problem statements (solution-first thinking)
  • ❌ Vague architecture ("we'll use a shell") — be specific (ink components, session registry, spawn.ts)
  • ❌ Ignoring existing work — always document impact on waves/milestones
  • ❌ No risk analysis — every architecture has risks, document them
  • ❌ Unbounded scope — draw the v1 line explicitly
  • ❌ Missing decision ownership — always say "needs sign-off from X"
  • ❌ No backward compatibility plan — users don't care about your replatform
  • ❌ Hand-waving timelines ("a few weeks") — be specific (2-3 weeks, 1 engineer full-time)

Red flags in proposal reviews:

  • "Users will love this" (citation needed)
  • "We'll figure out X later" (scope creep incoming)
  • "This is revolutionary" (tone ceiling violation)
  • No section on "What Stays the Same" (regression risk)
  • No risks documented (wishful thinking)

© FritzAndFriends, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .copilot/skills/architectural-proposals of FritzAndFriends/SharpSite.

Open the folder on GitHubat commit c35e5e0

Used in 2 other repositories

We found 3 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in FritzAndFriends/SharpSite, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Architectural Proposals next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Architectural Proposals compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Architectural Proposals this skillFritzAndFriends/SharpSite1452 repos~1.6kAutomated safety check: PassMIT
Doc Coauthoringaws-samples/sample-strands-agent-with-agentcore19540 repos~3.2kAutomated safety check: PassMIT
Audit Onboarding Proposalhoangnb24/repository-harness1.2k—~4kAutomated safety check: PassMIT
No Negative EchoLB623/no-negative-echo900—~965Automated safety check: PassMIT
GEO Service Proposal Generatorzubair-trabzada/geo-seo-claude11k—~3kAutomated safety check: NotesMIT
Counter Proposal Generatorzubair-trabzada/ai-legal-claude1.8k—~2.4kAutomated safety check: PassNone

Similar skills

  • Doc Coauthoring

    aws-samples/sample-strands-agent-with-agentcore

    Official

    Guide users through a structured workflow for co-authoring documentation.

    195 GitHub starsUsed in 40 repos~3.2k tokens
    Sales & SupportAuto-check passed
  • Audit Onboarding Proposal

    hoangnb24/repository-harness

    Use only when the user explicitly invokes $audit-onboarding-proposal.

    1.2k GitHub stars~4k tokensUpdated 7 days ago
    Sales & SupportAuto-check passed
  • No Negative Echo

    LB623/no-negative-echo

    Prevent 此地无银三百两式 residue: finalize artifacts without echoing rejected session-only alternatives into labels, metadata, commits, PRs, or handoffs.

    900 GitHub stars~965 tokensUpdated 1 mo ago
    Sales & SupportAuto-check passed
  • GEO Service Proposal Generator

    zubair-trabzada/geo-seo-claude

    Builds a client-ready AI-search-optimization proposal from an existing GEO audit, with pricing tiers, an ROI estimate and a markdown document ready to send.

    11k GitHub stars~3k tokensUpdated yesterday
    Sales & SupportAuto-check: notes
  • Counter Proposal Generator

    zubair-trabzada/ai-legal-claude

    Generates specific counter-proposals for every unfavorable clause, with replacement language, negotiation talking points, and a ready-to-send email template

    1.8k GitHub stars~2.4k tokensUpdated 6 mo ago
    Sales & SupportAuto-check passed
  • Task Profile

    techwolf-ai/ai-first-toolkit

    Mine the user's Claude Code + Cowork session history into a structured task profile, what they do with AI, how often, how successfully where friction lives, then propose atomic skills that would…

    132 GitHub stars~3.6k tokensUpdated 11 days ago
    Sales & SupportAuto-check passed

More from FritzAndFriends/SharpSite

All 18 skills in this repo
  • Client Compatibility

    FritzAndFriends/SharpSite

    Platform detection and adaptive spawning for CLI vs VS Code vs other surfaces

    145 GitHub starsUsed in 2 repos~1.3k tokens
    Auto-check passed
  • Distributed Mesh

    FritzAndFriends/SharpSite

    How to coordinate with squads on different machines using git as transport

    145 GitHub starsUsed in 2 repos~3.1k tokens
    Auto-check passed
  • Docs Standards

    FritzAndFriends/SharpSite

    Microsoft Style Guide + Squad-specific documentation patterns

    145 GitHub starsUsed in 2 repos~567 tokens
    Auto-check passed
  • Economy Mode

    FritzAndFriends/SharpSite

    Shifts Layer 3 model selection to cost-optimized alternatives when economy mode is active.

    145 GitHub starsUsed in 2 repos~1.3k tokens
    Auto-check passed
  • External Comms

    FritzAndFriends/SharpSite

    PAO workflow for scanning, drafting, and presenting community responses with human review gate

    145 GitHub starsUsed in 2 repos~3.1k tokens
    Auto-check passed
  • Gh Auth Isolation

    FritzAndFriends/SharpSite

    Safely manage multiple GitHub identities (EMU + personal) in agent workflows

    145 GitHub starsUsed in 2 repos~1.6k tokens
    Auto-check: notes

Categories

Questions about Architectural Proposals

What does Architectural Proposals do?

How to write comprehensive architectural proposals that drive alignment before code is written. Architectural Proposals is an agent skill from FritzAndFriends/SharpSite.

When should I use Architectural Proposals?

Architectural Proposals fits situations like: tasks that involve Proposals and quotes.

How do I install Architectural Proposals in Claude Code?

Run `npx skills add FritzAndFriends/SharpSite --skill architectural-proposals -a claude-code`. Or copy the skill folder (.copilot/skills/architectural-proposals in FritzAndFriends/SharpSite) into .claude/skills/architectural-proposals in your project. Claude Code loads it when a task matches its description.

How do I install Architectural Proposals in Codex?

Run `npx skills add FritzAndFriends/SharpSite --skill architectural-proposals -a codex`. Or copy the skill folder (.copilot/skills/architectural-proposals in FritzAndFriends/SharpSite) into .agents/skills/architectural-proposals in your project. Codex loads it when a task matches its description.

Can I use Architectural Proposals in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add FritzAndFriends/SharpSite --skill architectural-proposals -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/architectural-proposals, .gemini/skills/architectural-proposals, .github/skills/architectural-proposals and .opencode/skills/architectural-proposals in your project.

What does Architectural Proposals need to run?

SKILL.md names no scripts, command-line tools or credentials: Architectural Proposals is instructions for the agent only.

Does Architectural Proposals access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Architectural Proposals safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Architectural Proposals use?

Architectural Proposals is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Architectural Proposals use?

About 1.6k tokens (SKILL.md is roughly 6.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Architectural Proposals?

Skills that share tags, products or a category with Architectural Proposals: Doc Coauthoring (aws-samples/sample-strands-agent-with-agentcore, 195 stars), Audit Onboarding Proposal (hoangnb24/repository-harness, 1.2k stars), No Negative Echo (LB623/no-negative-echo, 900 stars) and GEO Service Proposal Generator (zubair-trabzada/geo-seo-claude, 11k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Architectural Proposals?

FritzAndFriends (a GitHub organization) maintains it in FritzAndFriends/SharpSite, which has 145 GitHub stars. The repository holds 18 skills in this directory. The repository was last updated on April 30, 2026.

Source: FritzAndFriends/SharpSite on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.