Tailored Build - nguyenhx2/agent-harness-bootstrap GitHub Wiki
Tailored Build
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spec-builder ends with a contract. harness-bootstrap begins with a codebase. The step between
them is where the team gets decided, and most agent kits do not have that step at all.
The problem it answers
The usual agent kit ships everything - every agent, a hundred skills, every rule and hook - installed before anyone has read the codebase. That costs more than it looks:
- You pay context for all of it, in every session. A rule that matches no file in your repo is a tax on every request.
- Seats end up with no owner. An agent nobody routes work to is a name that makes the routing table harder to read.
- The advice goes generic. Guidance true in any repository is rarely specific enough to act on in yours.
- Nothing is visibly load-bearing. When everything is installed, nobody can safely remove anything.
Completeness gets mistaken for fit. Only fit is worth paying for.
What decides what
The roster comes from evidence and nothing else: what the contract says must be built, what the codebase analysis found, and the answers only you can give.
flowchart LR
C[/"Codebase analysis"/]
S[/"The contract"/]
A["Your answers"]
B["Roster and flags"]
SE[/"Seats"/]
RU[/"Path-scoped rules"/]
SK[/"Skill shortlist"/]
C --> B
S --> B
A --> B
B --> SE
B --> RU
B --> SK
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class C,S,SE,RU,SK art
| Decided from | What it decides |
|---|---|
| The modules that actually exist | One dev agent each, scoped to real paths. No module, no seat. |
| The repo's purpose | Code, research, strategy or docs, in any combination. A research repo gets researcher and checker, a docs repo writer and checker, and none of them gets a test suite or a code review gate. |
| The contract and your answers | Which of the 18 seats are filled. A run installs 3 to 17 of the 18 seats, never all of them by default. |
| The manifests in your repo | Which skills are proposed. You choose from that shortlist. |
| The paths that exist | Which rules are path-scoped, which keeps most rule content out of the default session. |
The numbers are measured, not claimed
The leanest answers give 3 seats (a documentation or research repo). A code repo with databases, tests and a long-lived project gives 17.
scripts/check_numbers.py computes that range with the scaffolder's own selection function,
over every combination of the flags that gate an agent, so it cannot drift from a real run. Change
which agents are gated and every place that quotes the range, this page included, fails until it is
updated.
Discovery and wiring are two problems
flowchart TD
M[/"Your manifests"/]
P["Propose a shortlist"]
U{"You pick"}
N["/new-skill"]
W["/skill-wire to a seat"]
G[/"Graph node"/]
M --> P --> U
U -->|"a fit"| W
U -->|"nothing fits"| N --> W
W --> G
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- Skill Discovery - you cannot choose from a catalogue you have never read. It reads this project's manifests (Python, Ruby, .NET, Java and Kotlin, JavaScript, monorepo markers), works out the stack, and only then proposes. Marketplaces are a source, not an authority. Nothing installs unless you pick it.
/new-skill- when nothing fits a recurring workflow, it first decides whether the workflow earns a project skill at all (refusing is normal), then scaffolds one and lints it withskill-check.py./skill-wire- installed is not reachable. It connects a skill to the seat or command that will use it and records that as a node in the graph, not a convention in a document.
Because the wire is a node, harness-view shows which skills are wired and which merely sit on
disk, and assess reports the difference as a finding.
It is checkable
A seat nobody owns, a skill nobody is told to use and a rule that matches no file are all costs.
harness-view assess names all three:
harness-view assess .
"Tailored" is a word anyone can put in a README. Three to seventeen of eighteen, and a finding when a seat has no module is something you can check.
See also
- Flag Reference - what each answer turns on
- Agent Reference - the seats and when each is installed
- Harness View - the scoring engine