Omar SobhandClaude Opus 5
4358964c05
55 of 85 role skill bindings pointed at skills that were never authored,
so 10 of 11 team templates bound a smaller context bundle than their role
prompts assumed. Three roles bound nothing at all (gpu.bench_engineer,
threejs.shader_author, threejs.perf_engineer) while their prompts described
procedures they had no way to read.
The loader comment at team_template_loader.rs:167 already diagnosed this —
snake_case slugs in TOML against kebab-case skill files — and it was
half-fixed: the kebab names were corrected, the snake_case ones left.
It was invisible because both existing tests assert authored ⊆ referenced
(30/30, green) and the second explicitly declines to check the other
direction. So the failing half was the half nobody asserted.
Resolved every name by one of three explicit choices:
- 23 skills authored where the role genuinely needed the procedure
(gpu, threejs, research, analysis, frontend, mobile, backend, platform)
- renames onto authored skills where one existed in substance, including
the four-near-duplicate cases that collapse onto one real skill
- 22 aspirational references deleted — a binding an agent cannot read is
a promise, not a capability
Two tests now hold it. The unit test checks referenced ⊆ authored against
the files. The new integration test runs both loaders in boot order and
asserts the bindings survive the trip through the database, which is a
different question: resolution goes through skills_catalog rows, so a skill
file that exists but fails to ingest still leaves the role empty.
Negative controls: the unit test failed naming all 55; the integration test
fails naming the exact role when one name is reverted.
threejs.shader_author and .perf_engineer gained a second and third skill
after the collapse — pin_in_context pins idx < 2, so a role left with one
skill silently pins less than the policy intends.
Co-Authored-By: Claude Opus 5 <[email protected]>
55 lines
2.2 KiB
Markdown
55 lines
2.2 KiB
Markdown
---
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name: scientific-writing-conventions
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description: Structure, hedging and claim discipline for a technical write-up that will be read by people who will check it.
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when_to_use: You are drafting a paper, a technical report, or any document making empirical claims.
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tags: [research, writing]
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---
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# Write so a sceptic can check you
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The reader's question is "is this true?" Every convention below exists to let
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them answer it without asking you.
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## Structure
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```
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ABSTRACT problem, what you did, headline result WITH its number
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INTRO why this matters, what was missing, contributions as a list
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METHOD enough that a competent reader could reimplement it
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RESULTS what happened, including what did not work
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DISCUSSION what it means, what it does not, threats to validity
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```
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Contributions belong as an explicit list. If you cannot write three sentences
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each starting "we show that...", the work is not finished.
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## Hedge exactly as much as the evidence hedges
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Both directions are failures. "Our method improves retrieval" from one dataset
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overclaims; "may potentially suggest a possible improvement" for a result with
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tight confidence intervals underclaims and reads as though you do not trust your
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own experiment.
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Match the language to the strength:
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- measured, with intervals, replicated → *shows*, *demonstrates*
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- measured once, single configuration → *indicates on X*
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- consistent with, not directly tested → *is consistent with*
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## Every number carries its conditions
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A number without its dataset, configuration and variance is not a result. Put
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them in the sentence or the table, never in a paragraph three pages away.
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## Threats to validity is not a formality
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State the ways you could be wrong: one seed, one hardware target, a benchmark
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your method was tuned on, a baseline you implemented yourself. A reviewer will
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find these; a paper that names them first is far more credible than one that
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lets them be discovered.
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## Say what you did not do
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Scope limits are part of the contribution. "We do not evaluate on multilingual
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corpora" prevents a reader assuming you did and finding out later — which costs
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you far more credibility than the limitation itself.
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