Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add tikalk/adlc-team-skills --skill architect-specifygit clone --depth 1 https://github.com/tikalk/adlc-team-skillsWrote 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/tikalk/adlc-team-skills/architect-specify)<a href="https://agentmods.dev/skills/tikalk/adlc-team-skills/architect-specify"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/architect-specify/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/tikalk/adlc-team-skills/architect-specify"><img src="https://agentmods.dev/badge/skills/tikalk/adlc-team-skills/architect-specify.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Memory Poisoning · line 601 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
- medium Excessive Agency · line 220 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 223 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00040 | $0.05809 |
| Opus 5.5 | $0.00016 | $0.02324 |
| Sonnet 5.5 | $0.00008 | $0.01162 |
| Haiku 4.5 | $0.00004 | $0.00581 |
Grade A, and why
architect-specify 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 5d 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 — 652 lines — stays where its author put it; the contents beside it link to each section on GitHub.
architect-specify
What this skill does
Transform a PRD (Product Requirements Document) or high-level system description into well-documented Architecture Decision Records (ADRs) through interactive exploration and trade-off analysis.
Key Insight: Unlike direct architecture generation, this skill prioritizes discussion and exploration before committing to formal documentation. The goal is to surface trade-offs, validate assumptions, and make informed decisions collaboratively.
You act as a Solutions Architect facilitating an architectural discovery session. Your role involves:
- Exploring possible solutions and their trade-offs
- Asking clarifying questions to surface hidden requirements
- Proposing options with clear consequences
- Documenting decisions in MADR format once consensus is reached
When to use
Note: Routine decision capture is handled by team-boot's continuous capture mechanism, which writes lightweight drafts directly to
.adlc/drafts/. This skill is for interactive deep-dive exploration — when you want guided trade-off analysis, multi-option comparison, or structured decision facilitation before documenting.
- New projects: Starting system architecture from scratch
- Major changes: Significant architectural shifts requiring new decisions
- Documentation: Capturing verbal decisions as formal ADRs
- Team onboarding: Walking through architectural rationale with new members
When NOT to use:
- Brownfield projects: Use
/architect-initinstead to reverse-engineer from code - Minor updates: Use
/architect-clarifyfor ADR refinements - Feature-level: Feature architecture (if Spec Kit extension is also installed)
Process
User Input
$ARGUMENTS
You MUST consider the user input before proceeding (if not empty).
Examples of User Input:
"B2B SaaS platform for supply chain management with real-time inventory tracking""Mobile-first e-commerce app with offline support and social features""Legacy system modernization: migrate from monolith to microservices""IoT platform for smart home devices with edge computing requirements"
What ships with it
7 files 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.
- scripts/bash/ascii-generator.sh 18 KB runs code
- scripts/bash/common.sh 3.1 KB runs code
- scripts/bash/mermaid-generator.sh 8.9 KB runs code
- scripts/bash/setup-architect.sh 54 KB runs code
- scripts/powershell/ASCII-Generator.ps1 18 KB runs code
- scripts/powershell/Mermaid-Generator.ps1 8.9 KB runs code
- scripts/powershell/setup-architect.ps1 49 KB runs code
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.
- 5d ago Changed 60d6fd52159c
- 25d ago Changed 4c2021f74abc
- 26d ago Changed ca43fdf39881
- 1mo ago Changed · +6 lines · +15 tokens per session 6dd0b365f083
- 1mo ago Changed · -9 tokens per session dee3056beb86
- 1mo ago First seen · 646 lines · 34 tokens per session scan A 4e6ed8120f98
architect-specify is a skill published in the GitHub repository tikalk/adlc-team-skills (143 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 5,809 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
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decision-records
Use when a hard-to-reverse choice (database, framework, vendor, auth model) must be frozen as an immutable numbered ADR — the context that forced it, the options weighed, the decision, consequences both ways — or superseded without erasing history. NOT a meeting recap (that is meeting-notes), NOT standing project…
prompt-engineering
Use when one prompt must give the same right answer across reruns, models, and pasted-in hostile input: forcing a fixed schema, picking the few-shot set, ordering the prompt blocks, or the inline cases you run while tuning. NOT the agent loop, tools, or retrieval (that is building-agents), NOT a standing CI eval…
respect-the-oracle
Use when working against a test suite, spec, or graded harness you do not own - especially inside an automated loop scored on how many tests pass - and tempted to change the tests, weaken assertions, hardcode expected outputs, special-case inputs, or overfit the visible examples to turn things green.
refocusing
Use when a long-running agent may have lost the product outcome, when context was compacted, when work has crossed a major boundary, or when a fresh path-based trace is needed before the next consequential action. Not for fresh-session orientation, waking an idle seat, or checkpoints.