AI-DLC Context Pack Builder
Every Bolt starts with a choice nobody names out loud: how much context does the agent actually need? Get it wrong either way and the Bolt fails before it starts.
Agents fail Bolts for one of two context reasons, and both look like the agent's fault when they aren't. Starved of context, it invents assumptions. Drowned in a full repo dump, it burns its attention on boilerplate and still misses what mattered. AI-DLC Context Pack Builder is a free agent skill that assembles the minimum sufficient Context Pack for one Bolt or Unit of Work, audits it in both directions, and won't hand it over until it passes.
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AI-DLC Context Pack Builder is a free agent skill published by Viksya that assembles a minimum sufficient Context Pack for one AI-DLC Bolt or Unit of Work — Intent, scope boundary, architecture touchpoints, contracts and constraints, definition of done, and references — then audits the pack in both directions (starved of context, or drowned in unnecessary material) and states an explicit PASS verdict, or a short list of specific fixes, before handing it over. It is plain markdown with no dependencies, works in Claude Code or any agent harness that reads a system prompt, and is free to keep and share with attribution intact.
Both failures look like the agent's fault. Neither one is.
Agents fail Bolts for one of two context reasons, and both are avoidable before a single line of code gets written.
The skill's single job: given a stated Intent or Unit of Work, walk you through assembling the minimum sufficient Context Pack before execution starts — and refuse to bless a pack that is either starved or drowned.
One Context Pack. Six sections. A verdict you can enforce.
The skill gathers what it needs conversationally, in one pass, not a twenty-question interrogation — and inspects your repo directly where it's accessible, rather than asking. The output is a single markdown artifact with exactly these sections.
The Context PackThe quality gate — the skill's actual value. Before finalising, it audits the pack both directions. Starvation checks: could two reasonable engineers read this and build different things? Is any section empty or generic? Drowning checks: is anything included the Bolt doesn't touch? A pack over roughly two pages triggers a justification pass — every block must answer “what breaks if the agent doesn't see this?” If nothing breaks, it's cut. The skill states PASS, or a short list of specific fixes, and won't hand over a pack it would fail.
- Context Pack
- The single markdown artifact this skill produces for one Bolt or Unit of Work — one page, not forty — covering Intent, scope boundary, architecture touchpoints, contracts and constraints, definition of done, and references.
- PASS Verdict
- The skill's explicit, machine-checkable audit result. A pack that hasn't passed both the starvation and drowning checks is not handed over — the verdict is designed to be wired into a Claude Code hook or a CI check that blocks the Bolt from starting.
Three files. No scripts. Nothing to install.
The skill is deliberately lean, following current agent-skill authoring practice — the procedure and template load on demand, not a wall of instructions up front.
Context Pack Builder vs. the rest of the AI-DLC line.
This skill owns one layer: what the agent is handed before a Bolt starts. It is complementary to, never a replacement for, AWS's own orchestration tooling — and it is the deliberately thin counterpart to Viksya's paid, org-level instruments.
| Instrument | Question It Answers | Format |
|---|---|---|
| AI-DLC Context Pack Builder (this skill) | What's the minimum sufficient context for this one Bolt? | Free agent skill |
| AI-DLC Dictionary of Terms | What does this term mean? | Free web reference |
| Context Engineering Playbook | How do we build and govern the context AI-DLC depends on, across every Bolt? | PDF playbook |
| AWS aidlc-workflows & similar harnesses | How does the agent not forget mid-session? | Orchestration tooling |
For whoever is about to hand an agent a Bolt.
Assemble and pass/fail-check a Context Pack before starting a Bolt, instead of guessing what the agent needs.
Give teams a repeatable, enforceable starting-context procedure without writing one from scratch.
Wire the PASS verdict into a hook or CI check that blocks a Bolt from starting on a bad pack.
Get a free, immediate answer to “how much context does the agent need” while evaluating the deeper practice.
Hard cases — multi-team context, legacy systems, conflicting constraints.
Get the Context Engineering Playbook →Just starting AI-DLC adoption?
View the AI-DLC Starter Kit →Not sure you're ready?
Take the Adoption Readiness Assessment →New to the vocabulary? Intent, Unit of Work, Bolt, and human validation gates are all defined terms this skill uses throughout.
View AI-DLC Dictionary →What makes this a gate, not just a template.
What this skill is not.
This skill owns one layer — what the agent is handed before a Bolt starts. It is deliberately thin everywhere else.
What you need to run it.
Questions before your first Context Pack.
Is it really free, and is there a catch?
Yes, free to use and share with the attribution notice intact. It is not white-label and not for resale, but there's no paywall, trial period, or feature gate on the skill itself. This is a deliberate lead-generation exception to Viksya's usual practice of bundling skills only as paid-product value-adds.
What's the difference between this skill and the Context Engineering Playbook?
This skill assembles one Bolt's Context Pack and audits it against a pass/fail gate — the procedure and the gate, nothing more. The Playbook is the standing, org-level counterpart: the five knowledge artifact types as living team artifacts, file design patterns, brownfield extraction, the full anti-pattern catalogue, and a governance model that survives across every Bolt. Hit a hard case with the skill — multi-team context, legacy systems, conflicting constraints — and the Playbook is what you reach for next.
Does it work outside Claude Code?
Yes. It's plain markdown with no scripts and no dependencies, so it runs in Claude Code or any agent harness that reads a system prompt.
What happens if my Context Pack fails the quality gate?
The skill states its verdict explicitly — PASS, or a short list of specific fixes — and won't hand over a pack it would fail. Common fixes: naming architecture touchpoints instead of describing them abstractly, adding a verifiable definition-of-done criterion, or cutting pasted content that should be a pointer instead.
Does this replace AWS's aidlc-workflows or my existing orchestration setup?
No. It has zero orchestration or execution behaviour by design and is built to work alongside AWS's aidlc-workflows and similar harnesses, not in place of them. It owns one layer: what the agent is handed before a Bolt starts.
Why do you ask for my name and email before the download?
So Viksya can send you the download link and let you know when the skill or its companion instruments update. The file itself is delivered as a free ($0) product through the Viksya store; your details aren't required to use the skill once you have it, and it remains free to share onward with the attribution notice intact.
Published free, kept portable on purpose.
Published free by Viksya (viksya.com) — decision frameworks for AI transformation and AI-DLC adoption. AI-DLC (AI-Driven Development Life Cycle) is a methodology defined by AWS. Viksya is not affiliated with or endorsed by AWS. Free to use and share with this notice intact. Not for resale or white-label use.
Source available on GitHub for developers who'd rather grab the raw files directly. (Placeholder link — repo not yet published.)
Give your next Bolt a Context Pack that passes.
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